Machine Learning Engineer Remote Jobs in Hawaii (US)
This page tracks remote machine learning engineer openings that are location-eligible for Hawaii.
This page tracks remote machine learning engineer openings that are location-eligible for Hawaii.
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Save the Children works in countries around the world to create positive, lasting changes in the lives of children. The international nonprofit organization env
Title: Managing Director, Campaign Strategy & Infrastructure (M3) Location: United States remote Job Category: Advocacy Campaigns & Engagement Requisition Number: MANAG008221 Full-Time Job Description: Save the Children Action Network Save the Children Action Network ("SCAN") - a 501(c)(4) organization - is the political advocacy arm of Save the Children. We are building bipartisan support to make sure every child has a strong start in life. We're doing this by advocating statewide and federally for high-quality early learning and ending child hunger in the U.S., the safety of children arriving at the southern U.S. border and educating and protecting kids around the world. The Role As the Managing Director, Campaign Strategy & Infrastructure, you will play a critical role in supporting the Head of SCAN in advancing SCAN's mission and strategic priorities. Working in close partnership with the Head, you will contribute to the development and execution of SCAN's campaign strategy, with a particular focus on building the infrastructure, systems, and tools required to run effective advocacy, electoral, and community-based campaigns in states nationwide. You will lead the design and implementation of scalable campaign frameworks, training programs, and operational systems that enable staff, volunteers, and grassroots advocates to mobilize effectively and work in a coordinated, high-impact way. In collaboration with the Head, Regional Directors and cross-functional partners, you will ensure campaigns are strategically aligned, well-executed, and positioned to drive engagement and influence policy outcomes at both the state and federal levels. Your work will be central to strengthening organizational cohesion, improving campaign effectiveness, and translating strategy into execution across SCAN's advocacy and electoral efforts. Location Hybrid - Washington DC, Fairfield, CT, Lexington, KY office locations Remote - United States What You'll Be Doing (Essential Duties) - not inclusive of all role responsibilities. May be subject to change. Campaign Strategy & Infrastructure Leadership (30%) - Support the development and operationalization of SCAN's campaign strategy by designing and continuously improving systems and ways of working. - Build and manage scalable campaign infrastructure-including planning tools, standards, and operating procedures-to enable consistent, high-quality execution across teams. - Coordinate closely with Campaigns, State, Elections, Constituency Engagement, and Data teams to align priorities, sequencing, and resource allocation in support of strategic objectives - Establish processes to evaluate campaign performance, capture learnings, and strengthen long-term organizing and advocacy effectiveness. - Support campaign readiness and rapid-response capabilities during key advocacy and electoral moments, ensuring teams are equipped to mobilize effectively. Team Leadership & Operational Management (25%) - Lead, develop, and coach a high-performing team - Set clear goals, performance expectations, and accountability frameworks aligned with the Head's strategic priorities and overall organizational outcomes - Foster a collaborative, inclusive, and high-performing team culture that prioritizes integration, innovation, and continuous improvement - Represent SCAN in cross-divisional initiatives and external engagements, reinforcing alignment with strategic objectives and elevating campaign impact - Support fundraising, donor engagement, and strategic communications by clearly articulating SCAN's organizing model, campaign approach, and measurable results Training, Leadership Development & Organizing Capacity Building (25%) - Lead SCAN's approach to building organizing capacity across staff, volunteers, and partners. - Oversee the design and delivery of training programs that strengthen capabilities across advocacy, elections, volunteer engagement, and community organizing. - Ensure training curricula and learning experiences build durable organizing skills and develop a strong pipeline of grassroots and organizational leaders. - Partner with internal teams and external organizations to expand training partnerships, represent SCAN in key forums, and support shared learning initiatives. - Develop systems for knowledge sharing and continuous learning, enabling best practices and consistent approaches across campaign teams. Cross-Functional Integration & Organizational Alignment (20%) - Partner with senior leaders across divisions to ensure campaign infrastructure and engagement strategies are aligned with broader organizational priorities, including policy, programs, and fundraising. - Facilitate cross-functional planning processes that integrate constituency engagement, volunteer mobilization, electoral activity, and advocacy priorities. - Work closely with programmatic teams to align SCAN's campaign presence with programmatic state footprints, ensuring coordinated, mutually reinforcing impact. - Translate campaign insights and operational data into strategic reporting, campaign readiness assessments, and recommendations to inform organizational decision-making. Required qualifications for the role - Minimum of a bachelor's degree or equivalent experience, plus at least 10 years of relevant experience on Capitol Hill, in non-profit advocacy, campaign organizing - Demonstrated experience leading complex, multi-channel advocacy, electoral, grassroots, or organizing initiatives - Proven effective leader and people manager with experience developing and leading high performance cross functional teams - Proven ability to create effective grassroots campaigns - Experience creating or managing training programs, leadership growth, volunteer involvement, or building organizing skills - Strong strategic planning, operational management, and cross-functional collaboration skills - Experience using data, metrics, and reporting to inform strategy and evaluate impact - Willingness and ability to travel up to 15-20% domestically - Professional proficiency in MS Office suite - Professional proficiency in spoken and written English Compensation Save the Children Action Network is offering the following salary ranges for this position, dependent on candidate location: - Geo 1 - NY Metro, DC, and other locations with labor costs significantly above national average: Target Salary for this position is $143,650 - $160,550 base salary - Geo 2 - Locations around the US National Labor Cost Average: Target Salary for this position is $130,900 - $146,300 base salary - Geo 3 - Locations significantly below the US National Labor Cost Average: Target Salary for this position is $116,875 - $130,625 base salary The salary ranges listed above are for US based candidates. For candidates located outside of the US, salary ranges will be based on the salary scales of the local employer of record. Actual base salary may vary based on, but not limited to, relevant experience, base salary of internal peers, business sector, and geographic location (more information on job structure is available here). About Us We are looking to build a diverse, equitable and inclusive team at Save the Children Action Network. We offer a range of outstanding benefits to support this goal: - Flexible schedules and time off: Flexible schedules, generous PTO, 11 paid holidays plus 2 floating holidays and hybrid working opportunities - Health: Competitive health care, dental and vision coverage for you and your family - Family: A variety of paid leaves: caregiver, parental/adoption, critical child illness and fertility benefits - Employee Rewards Program: Annual merit increases and/or additional incentives for eligible employees - /Retirement: A retirement savings plan with employer contributions (after one year) - Wellness: 15 safety and wellness days annually (if hired on or after July 1, safety and wellness days prorated to 8 days), mental health benefits and support through Calm and company-hosted events - Employee Assistance Program: free and confidential assessments, short-term counseling, referrals, and follow-up services - Learning & Growth: Access to internal and external learning & development opportunities and mentorships Click here to learn more about how Save the Children Action Network will invest in you. Save the Children Action Network is committed to conducting its programs and operations in a manner that is safe for the children it serves and helping protect the children with whom we are in contact. All Save the Children Action Network representatives are explicitly prohibited from engaging in any activity that may result in any kind of child abuse. Save the Children Action Network is committed to minimizing safety and security risks for our valued employees, ensuring all are given training, support and information to reduce their risk exposure while maximizing the impact of our programs for children and families. Our shared duty, both agency and individual, is to seek and maintain safe working conditions for all.
Block builds simple, powerful tools that make progress towards an economy that’s truly open to all.
Role Description Block is building toward one of the most ambitious technical visions in our history: an AGI-enabled entity that fundamentally transforms how we deliver economic empowerment. We're assembling a world-class team of AI experts to design and ship autonomous agents and agentic workflows that operate across Square, Cash App, and the broader Block ecosystem. This work is about creating solutions—you'll be building AI that acts, decides, and completes real tasks for real users from across all of Block's business functions. As a Principal Engineer, you'll join as a senior individual contributor with significant technical leadership responsibilities. - Ship, architect, build, and own end-to-end delivery of autonomous agents and agentic workflows that deliver real business value for Block, ensuring reliability, safety, and performance at scale. - Design agent orchestration systems including planning, tool use, memory, evaluation, and multi-agent coordination at production scale. - Integrate and optimize frontier LLMs into agent architectures, making decisions on model selection, fine-tuning, prompt engineering, and context retrieval strategies. - Drive deeper model optimization work (fine-tuning, distillation, RLHF) where it unlocks agent capability or efficiency. - Lead detailed technical planning by breaking down ambitious objectives into concrete, sequenced tasks with clear ownership and execution paths. - Provide technical mentorship and guidance to engineers across experience levels, elevating team capabilities through code review, pairing, and knowledge sharing. - Partner closely with technical and non-technical stakeholders to translate business objectives into agent-powered product experiences. - Keep Block at the frontier by continuously evaluating emerging AI capabilities and making pragmatic tradeoffs across model performance, latency, cost, and user experience. - Foster a culture of technical excellence, high-quality delivery, rapid experimentation, and learning within your team and beyond. Qualifications - 15+ years of experience in software engineering or machine learning, with recent professional experience building autonomous agents or agentic workflows in production. - Deep experience building autonomous agents or agentic workflows in production environments—not just prototypes or demos. - Fluency in the core primitives of agentic systems: context management, planning, tool use, memory, evaluation, and multi-step reasoning. - Experience bringing frontier LLM capabilities into production products, with hands-on experience in prompt engineering, retrieval-augmented generation, and model optimization. - A track record of taking AI-powered products from zero to scale in fast-paced, product-driven environments, with the judgment that comes from operating in production. - Strong software engineering fundamentals with the ability to write production-quality code and make sound architectural decisions. - Experience providing technical leadership within teams—you've shaped technical direction, driven execution, and elevated others. - Product-minded engineering approach—you think in terms of user outcomes, not just model metrics. - Excellent collaboration and communication skills, with ability to build alignment across engineering, product, and design. - Comfort navigating extreme ambiguity in a domain that's evolving weekly. - Alignment with Block's mission of economic empowerment and using technology to create access and opportunity. Bonus Points For - Experience at leading AI organizations with a track record of translating research into production agent systems. - Background building or scaling agentic products at startups (including early-stage or pivoting companies). - Experience with model fine-tuning, distillation, or RLHF to improve agent performance. - Familiarity with agent evaluation, safety, and alignment challenges in production contexts. Benefits - Remote work - Medical insurance - Flexible time off - Retirement savings plans - Modern family planning
We are Oregon's only public academic health center. In addition to caring for patients, we lead groundbreaking research. We also train the next generation of health care professionals. As Portland's largest employer, we give you opportunities to learn and advance in a system of hospitals and clinics across Oregon and Southwest Washington. All are welcome. OHSU welcomes people of all ages, ethnicities, genders, national origins, religions and sexual orientations. We are striving to build an anti-racist, multicultural institution and encourage people with diverse backgrounds to apply. To request reasonable accommodation, contact askhr@ohsu.edu.
Role Description A postdoctoral fellow position in myelin biology is available in the laboratory of Ben Emery in the Jungers Center for Neurosciences Research at Oregon Health and Science University. The position is for the bioinformatic investigation of central nervous system remyelination and neuroglial interactions in mouse models and human datasets. - Run a research project investigating CNS cell interactions during remyelination, including the use of genetic models of demyelination, snRNA-sequencing, and histological analyses. - Regularly attend and contribute to laboratory and departmental meetings. - Contribute to the preparation of scientific manuscripts. - Keep abreast of the scientific literature relevant to the project. Qualifications - PhD in Neuroscience. - Relevant skills in rodent models of CNS injury, bioinformatics, and machine learning approaches to microscopy analysis. - Excellent documentation and written communication skills. - Able to perform the essential functions of the position with or without accommodation. Benefits - Oregon's only public academic health center. - Opportunities to learn and advance in a system of hospitals and clinics across Oregon and Southwest Washington. Company Description In addition to caring for patients, we lead groundbreaking research. We also train the next generation of health care professionals. All are welcome. OHSU welcomes people of all ages, ethnicities, genders, national origins, religions, and sexual orientations. We are striving to build an anti-racist, multicultural institution and encourage people with diverse backgrounds to apply. To request reasonable accommodation, contact askhr@ohsu.edu .
At Nsight Health, you’ll be part of a fast-growing organization that sits at the intersection of healthcare, technology, and compassion. We’re looking for people who care deeply about improving patient lives and building the future of connected care. Our team culture is collaborative, agile, and purpose-driven. Every role—from clinical operations and customer success to marketing, technology, and leadership—directly contributes to improving how healthcare organizations care for their patients.
Role Description We are seeking an AI Engineer to own the technical operation and continuous improvement of Nsight's AI phone agents — the automated voice systems handling outbound and inbound patient calls across RPM and care management programs. This is not a passive vendor oversight role. You will be the hands-on operator of the system: fluent in the provider's UI, API, and webhook integrations, holding them to quality and HIPAA compliance standards, and driving measurable improvement in clinical voice interaction outcomes. Reporting to the VP of Engineering, you will work closely with the EVP of Patient Experience and the R&D team to: - Configure and tune AI phone agents - Build PHI-safe audio processing pipelines - Architect quality intelligence systems - Automate downstream action on detected failures This role operates inside an organization that runs at an AI-to-human engineering output ratio most teams haven't attempted. AI agents are first-class contributors to the pipeline here. You are expected to build and operate within that model from day one. AI Fluency Requirement - Non-Negotiable Nsight Health is an AI-first organization. Every member of our leadership and operations team is expected to actively use AI tools in their day-to-day work - not as a novelty, but as a core productivity multiplier. This role requires genuine curiosity about AI, comfort experimenting with tools like Claude, ChatGPT, and workflow automation platforms, and the judgment to know when AI helps and when it doesn't. If AI makes you uncomfortable, this is not the right role. Key Responsibilities - Vendor & Provider Management: Serve as the technical liaison between Nsight and the IVA provider; translate clinical and operational requirements into clear direction for the provider and their capabilities back to internal stakeholders. Manage day-to-day performance against quality and HIPAA compliance standards and drive resolution when expectations aren't met. Define acceptance criteria and build layered test harnesses for all provider releases before they touch production clinical workflows or patient data. - AI Phone Agent Configuration & Optimization: Rapidly become an expert in the provider platform; configure and tune AI phone agents to meet clinical and operational goals. Actively influence the provider's NLU engine design — working alongside their team on tuning, accuracy, and continuous iteration until the IVA agents are best in class for clinical voice interactions. - Alerting & Quality Intelligence: Build and own the alerting layer: continuously scrape provider data, classify failure patterns, and fire automated alerts before issues require manual intervention. Architect AI-driven quality intelligence pipelines that surface failures proactively and route them to the right owner without manual triage. - PHI-Safe Pipeline & Compliance: Build PHI-safe audio processing pipelines using local speech-to-text so recordings never leave the infrastructure, with PHI redacted in memory before anything reaches storage. Maintain HIPAA-compliant data handling across all AI pipelines and BAA-covered third-party integrations. - AI-Native Tooling: Build the tooling the work requires — semantic search, vectorized data processing, automated alerting, or whatever approach best fits the problem. Outcomes matter, not the stack. The Impact You’ll Make - Patient Experience at Scale: The AI phone agents you configure and optimize are the first touchpoint for thousands of Medicare patients across 350+ clinics — your work directly shapes their care experience. - Compliance by Design: By building PHI-safe pipelines and holding the provider to documented HIPAA standards, you protect both patients and the organization from the ground up. - AI Operations Pioneer: You will define what production-grade AI voice operations looks like in a regulated healthcare environment — building the alerting, quality intelligence, and automation infrastructure that keeps it running without manual oversight. Qualifications - 4+ years of ML or AI engineering experience, with at least 2 years working directly with production LLM integrations in systems serving real users — not research models or demos - Deep NLP/NLU expertise: intent recognition, entity extraction, utterance design, and understanding of how NLU accuracy degrades in production without active maintenance - Voice AI experience in a production environment: speech-to-text, TTS, or conversational AI with NLU at its core - NLU training and tuning in production: managed training data pipelines, designed utterance sets, measured accuracy against real interactions, and iterated based on results - Healthcare data fluency: claims data, RPM vitals streams, EHR data models, and experience running AI on HIPAA-covered patient data - Hands-on experience with multi-agent system design including specialist agents, adversarial review layers, and orchestration patterns at scale - Prompt engineering for classification and structured output at production volume: severity calibration, JSON response enforcement, and iterative refinement driven by precision/recall data - PHI-safe AI pipeline design: in-memory redaction, local inference where required, and data minimization patterns - LLM platform fluency: Anthropic Claude API, AWS Bedrock, and OpenAI API - Vector and embedding infrastructure: pgvector, Pinecone, or comparable - Agent and orchestration frameworks: LangChain, LlamaIndex, CrewAI, or equivalent - PostgreSQL and SQL fluency; alerting and issue routing tooling (Jira API, Slack webhooks, PagerDuty, or equivalent) - Telephony platform familiarity: VoIP systems such as Five9, Twilio, or equivalent - Daily, demonstrated use of Claude Code, GitHub Copilot, or equivalent AI-assisted development tools. This is a hard requirement. Preferred - Voice and speech tooling: Whisper, Deepgram, AWS Transcribe, or TTS providers; experience in a clinical or regulated audio context - Tray.io workflow automation and integration experience - AWS Glue and Apache ecosystem experience (Airflow, Kafka, Spark) for data pipeline and orchestration work - Bachelor's degree in Computer Science, Engineering, or a related field. Relevant experience will be weighted heavily over educational credentials alone. Compensation & Benefits - Competitive base pay: $160,000 - $165,000 annually. - Additional Compensation: Performance-Based Bonus: Eligible for an annual bonus based on company and individual performance. - Benefits Include: - PTO Accrual Based - Medical, Dental, Vision, and supplemental insurance options - 401(k) Plan with 3.5% Company Match - Company-provided equipment Join Our Mission-Driven Team At Nsight Health, you'll be part of a fast-growing organization that sits at the intersection of healthcare, technology, and compassion. We're looking for an AI Engineer who takes pride in production-grade work, operates with precision in a regulated environment, and wants their expertise to directly improve how patients experience care.
Transforming behavioral health through technology with a human touch
• Design, train, fine-tune, and evaluate deep learning, classical ML, and foundational GenAI models to drive core product features. • Build, scale, and maintain robust ML pipelines for continuous training, evaluation, and real-time/batch inference using modern MLOps frameworks. • Collaborate with backend and frontend teams to integrate AI models into microservices, ensuring low latency, high availability, and optimal resource utilization. • Architect scalable data pipelines for preprocessing, vectorizing, and ingestion of massive structured and unstructured datasets. • Implement rigorous evaluation frameworks for model alignment, bias mitigation, guardrailing, and cost/latency optimization (e.g., quantization, distillation). • Provide technical leadership, conduct thorough code reviews, and mentor junior/mid-level engineers on best practices in software craftsmanship and ML engineering.
• Design, build, and optimize ML/DL models for production-scale audio deepfake detection, ensuring robustness across diverse real-world conditions including compression artifacts, noise, telephony, and streaming pipelines. • Partner with clients to develop a deep understanding of their production environments and define model performance criteria. • Investigate failure cases in client environments, build custom evaluation frameworks, and implement mitigation strategies spanning both Engineering and AI. • Design and execute structured experimentation roadmaps aligned with client requirements and proactive system resilience goals. Translate findings into clear and actionable insights. • Monitor, measure, and report on model performance in production using data analytics and AI observability tools (e.g. Datadog, Metabase). Identify degradation trends, data drift, and emerging threat patterns before they impact client outcomes. • Build and maintain dashboards and analytics pipelines that surface model health metrics, enabling data-driven decisions across AI, Engineering, and Product teams. • Collaborate with cross-functional partners — Applied Scientists, Deployment Engineers, and Product teams — to deploy scalable, production-grade models with clear performance benchmarks and monitoring in place.
• Tune and optimize ML/DL models for production-scale audio deepfake detection. • Investigate failure cases in the client environment, build custom evaluation frameworks, and implement mitigation strategies for model robustness. • Drive model iteration for performance under a variety of real-world environments, e.g. compression artifacts, noise, telephony, and streaming pipelines. • Present technical findings and model performance insights to internal stakeholders. • Interface with Product and Engineering teams to build a deep understanding of the production environment and incorporate relevant evaluations for performance assessment.
Role Description We're hiring a Senior AI Developer / AI Architect to lead the technical direction of our AI initiatives. This is a greenfield opportunity—you won't be inheriting legacy systems or maintaining someone else's architecture. You'll be designing and building from the ground up. You'll own the full stack of decisions: - Platform selection - Model strategy - RAG architecture - Agent design - Observability - Cost optimization If you've been waiting for a role where you can build something meaningful without fighting through layers of tech debt and organizational inertia, this is it. Qualifications - Bachelor's degree in Computer Science, Data Science, Engineering, or related field; or equivalent practical experience - 5+ years in AI/ML development - 2+ years in architectural leadership or technical lead roles - Proven track record architecting and deploying AI/ML systems in production environments - Experience designing systems that handle sensitive data with appropriate security and compliance controls Requirements - Deep expertise in AWS Bedrock and/or Google Vertex AI - Proficiency with large language models (Claude, GPT, Gemini) and their APIs - Hands-on experience building RAG systems end-to-end—including document ingestion, parsing, chunking strategies, embedding models, vector databases, and retrieval optimization - Experience with vector databases (Pinecone, pgvector, or similar) - Strong background in prompt engineering and LLM integration patterns - Hands-on experience with agentic patterns: MCP (Model Context Protocol), tool-use/function calling, ReAct, Plan-and-Execute, or similar approaches - Experience with orchestration frameworks (LangGraph, LangChain, or similar) - Experience designing and implementing AI observability and evaluation systems - Track record of managing AI infrastructure costs and optimizing token economics - Proficiency in Python and/or TypeScript for AI/ML development - Experience designing secure, scalable API ecosystems (REST, GraphQL) Benefits - Competitive salary and benefits package - Dynamic and innovative work environment - Opportunities for professional growth and development - Remote work flexibility
Role Description RxBenefits is hiring! We are adding a Senior Software Engineer (Software Engineer III) to the growing application development team at our Birmingham, AL headquarters. As a senior engineer, you will be responsible for designing and building the data pipelines, streaming infrastructure, and machine learning systems that power our rapidly growing business. You will also be a thought leader across the technology organization that champions modern data engineering practices. This is an exciting opportunity for a forward-thinking professional who can conceptualize, deliver, and support the data-driven technology that our employees and partners need to succeed. - Design and build real-time data pipelines and streaming infrastructure using Apache Flink and related technologies - Develop and maintain stateful processing layers for fast, reliable data enrichment - Design and build backend services in Golang, Java, or Python that process data reliably at scale - Build, train, and deploy traditional ML models to surface insights and power data-driven features, owning the workflow from feature engineering through production monitoring - Build scalable services that integrate ML model inference, feature stores, and real-time scoring into production workflows - Build tooling and infrastructure for data quality, validation, and pipeline observability - Implement monitoring and observability for data pipelines and ML models, including data quality metrics and drift detection - Ensure solutions meet enterprise standards for reliability, security, compliance, and observability - Partner with product and data teams to translate business problems into ML and data engineering solutions - Participate in architectural design and recommend technical solutions - Review and collaborate with other engineers on their code - Mentor and share knowledge within the team and across the department Qualifications - Bachelor’s degree in computer science, mathematics, engineering or another related field - 6-8 years of professional experience in software development - Strong proficiency in one or more of the following backend languages: Golang, Java, or Python - Solid understanding of RESTful API design, microservices, and distributed systems - Strong foundation in data structures, algorithms, concurrency, and performance optimization - Familiarity with relational and NoSQL databases and their performance characteristics - Hands-on experience (1-3 years) building and evaluating traditional ML models (XGBoost, Random Forests, Logistic Regression) in production environments - Familiarity with the end-to-end ML workflow including feature engineering, model selection, training, evaluation, and production monitoring - Experience handling sensitive data (PII/PHI) in data pipelines, including masking, redaction, or de-identification - Experience building and deploying services on AWS - Experience with Agile development methodologies - Strong communication and presentation skills - Effective working independently or collaboratively within a team - Ability to think strategically and execute with urgency Requirements - Experience building high-throughput data pipelines at scale using Apache Flink, Kafka Streams, or similar frameworks - Experience evaluating ML model performance in production, including data drift and model degradation - Proficiency in AWS services: Sagemaker, Bedrock, MSK, Glue, EMR, DynamoDB, EC2, Lambda, S3, and IAM - RocksDB or similar embedded storage engines - Caching and in-memory database technologies - Asynchronous/multi-threaded programming patterns - Experience working in regulated industries (healthcare, finance, insurance) - Knowledge of governance frameworks around data privacy (HIPAA, SOC2, GDPR, etc.) - Frontend development with NextJS or React Benefits - Remote first work environment - Choice of a HDHP or PPO Medical plan, we pay 100% of the premium for the HDHP for you and your eligible family members - Dental, Vision, Short- and Long-Term Disability, and Group Life Insurance that we also pay 100% of premiums (for your family too on Dental and Vision) - Additional buy-up options for Short- and Long-Term Disability and Life Insurance - 401(k) with an employer match up to 3.5% available after 60 days - Community Service Day to give back and support what you love in your community - 10 company holidays including MLK Day, Juneteenth, and the day after Thanksgiving plus a floating holiday to use as you like - Reimbursements for high-speed internet, we’ll send you a computer and monitors to help you do your best work - Tuition Reimbursement for accredited degree programs - Paid New Parent Leave that can be used for adoption or birth - Pet insurance to protect your furbabies - A robust mental health benefit and EAP service through Spring Health to support you when you need it most
Role Description The GenAI Engineer is a core technical contributor responsible for designing, building, deploying, and managing AI and Machine Learning solutions across enterprise environments. This role focuses on implementing both classical ML and modern Generative AI workloads, including agent-based systems, Retrieval-Augmented Generation (RAG), and LLM-driven pipelines. The engineer ensures all AI solutions are scalable, secure, governed, and aligned with enterprise architecture and operational requirements. Key Responsibilities - Design, build, and deliver end-to-end AI/ML solutions—from experimentation and prototyping to production deployment. - Develop AI solutions using Azure AI Foundry, Azure OpenAI, Azure Machine Learning, and related Azure AI services. - Build agent-based architectures using frameworks such as LangChain, LangGraph, Semantic Kernel, and MCP-style orchestration patterns. - Design and optimize prompt engineering strategies, RAG pipelines, embeddings, vector search, and knowledge-grounding workflows. - Build, train, evaluate, and deploy classical ML and GenAI models using Azure Machine Learning, including pipelines, feature engineering, model registry, and experiment tracking. - Implement MLOps and LLMOps practices including CI/CD, automated testing, responsible deployment, model monitoring, drift detection, and performance optimization. - Integrate AI solutions securely with enterprise systems, APIs, and event-driven architectures. - Embed Responsible AI principles—fairness, explainability, transparency, and human-in-the-loop controls—into solution design and development. - Collaborate closely with Data Engineers, AI Architects, Security teams, and business stakeholders to deliver scalable, compliant AI solutions. - Provide engineering guidance, mentor junior team members, and contribute to reusable components, shared libraries, and engineering best practices. Qualifications - Strong hands-on experience building and deploying AI solutions on Azure, including Azure AI Foundry, Azure OpenAI, Azure Machine Learning, Azure AI Search, and Cognitive Services. - Solid understanding of machine learning concepts including feature engineering, model training, evaluation, hyperparameter tuning, and operational deployment. - Experience deploying both predictive ML and GenAI solutions in enterprise settings. - Hands-on experience with LLM-based system development, agent orchestration, and tool automation using frameworks such as LangChain, LangGraph, Semantic Kernel, and MCP-style agent communication patterns. - Experience implementing RAG pipelines, embeddings, vector databases, and document ingestion architectures. - Strong understanding of LLM constraints, prompt optimization, hallucination mitigation, and output-validation strategies. - Experience implementing CI/CD for ML and LLM workloads, including testing, monitoring, versioning, and automated deployment. - Familiarity with Azure DevOps pipelines, Git-based workflows, and cloud-native deployment automation. - Understanding of cloud-native patterns, containerization, and scalable AI infrastructure. - Knowledge of identity, access management, secrets management, and secure deployment practices for AI systems. - Familiarity with Responsible AI frameworks and enterprise governance models. - Ability to translate business problems into practical, scalable AI solutions. - Strong communication and cross-functional collaboration skills. - Experience working within Agile environments (Scrum, Kanban) delivering iteratively and incrementally. Preferred Certifications & Training - Databricks Certified Generative AI Engineer Associate - Microsoft Azure AI Engineer Associate - Azure Machine Learning Certification - Azure Data Scientist Associate (optional) - MLOps or LLMOps training - LangChain/GenAI specialization coursework Role Impact This role is central to building and scaling enterprise-ready AI capabilities. It enables the development of secure, governed, high-performing AI systems that support organizational innovation, automation, and decision intelligence. Why This Opportunity Is Attractive - Work with cutting-edge AI technologies and modern GenAI frameworks. - Lead hands-on development of AI systems deployed at enterprise scale. - Collaborate with cross-functional experts across architecture, engineering, and security. Why NTT Data? Empowerment and rewards are the cornerstone of our career development model. We are a young, fast-growing company, with a highly innovative and entrepreneurial spirit, because of this professional experience and growth will be unmatched. Our talent and positive attitude allow us to transform our goals into achievements, and projects into realities.
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Python, PyTorch, AI/ML, Microservices