Machine Learning Engineer Remote Jobs in Virginia (US)
This page tracks remote machine learning engineer openings that are location-eligible for Virginia.
This page tracks remote machine learning engineer openings that are location-eligible for Virginia.
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• Design, develop, and deploy AI/ML solutions to modernize core pharmacy platforms, with a focus on scalability, reliability, performance, and security • Leverage Generative AI, LLMs, and agentic AI frameworks to automate and enhance pharmacy workflows and decision-making processes • Collaborate with business and technical stakeholders to understand pharmacy domain requirements and translate them into robust AI/ML-driven technical solutions • Contribute to architecture and technical design of AI/ML pipelines, including model selection, data integration, and deployment patterns • Establish and maintain AI/ML engineering standards, best practices, and quality assurance processes • Conduct code reviews, provide constructive feedback, and mentor engineers on modern AI/ML engineering practices • Partner with cross-functional teams including data scientists, product managers, platform engineers, and pharmacy domain experts • Translate legacy system modernization needs into scalable AI applications that enhance products, workflows, and operational efficiency • Monitor and optimize AI/ML model performance, resource utilization, and platform reliability • Collaborate with DevOps and infrastructure teams to ensure secure, scalable deployment and operations of AI/ML solutions • Stay current with advancements in AI/ML frameworks, Generative AI, LLMs, and pharmacy technology modernization
Founded in 2004 and led by CEO Steve Chapman, Natera is a company in the biotechnology market that offers genetic testing and diagnostics on a global scale. Ope
Senior AI-Machine Learning Engineer US Remote Role Overview The Senior AI/ML Engineer is responsible for designing, building, and deploying Natera’s Generative AI and Machine Learning platforms. The role needs excellent hands-on engineering excellence to build robust, compliant, and efficient Generative AI and ML platform components. This role requires deep expertise in Generative AI and machine learning engineering at scale, with a passion for building robust, compliant, and high-performance systems that directly impact patient outcomes and clinical innovation. You will design, build, and scale enterprise-grade AI/ML systems that power internal workflows (R&D, Lab Ops, Clinical Trials, Billing, Patient/Provider engagement) and external-facing AI/ML platforms. You will design and build cutting-edge AI solutions leveraging agentic architecture, retrieval-augmented generation (RAG), vector search, feature stores, LLMOps, experimentation, observability, and compliance-first AI pipelines. You will be responsible for development of a production-ready Generative AI and MLOps platform with reusable components used to deploy multiple AI solutions across Natera’s business units. You will also develop clear standards and best practices established for AI/ML development across the organization. Key Responsibilities Platform Development - Design and implement foundational GenAI services: vector search, prompt tuning, agent orchestration, document extraction, context/memory services, model/endpoint registry, feature/embedding stores, guardrails, and evaluation pipelines - Build the underlying infrastructure for autonomous and semi-autonomous AI agents including support for agent collaboration, reasoning, and memory persistence, enabling continuous context-aware execution - Build standardized APIs/SDKs that make it easy for product teams to compose, deploy, and monitor Generative AI workloads. - Ensure platform components meet enterprise-grade requirements for scalability, latency, multi-region resilience, and cost efficiency Generative AI Enablement - Stand up LLM runtimes with token/rate governance, caching, and safe tool-use - Implement RAG at scale: ingestion pipelines, chunking/embedding policies, hybrid search, relevance/risk scoring, and feedback loops - Build agent orchestration (single & multi-agent) with planning, tool routing, shared/persistent memory, and inter-agent communication - Integrate tooling and APIs that allow agents to interact with internal systems, retrieve data securely, and take action under strict controls - Collaborate with research teams to prototype and productionize multi-agent architectures for workflow automation, report generation, and data synthesis. Infrastructure & Automation - Implement cloud-native infrastructure for large-scale model training and serving using Kubernetes, MLflow, Terraform, and AWS-native services - Automate data and model pipelines for RAG, LLM fine-tuning, and agent orchestration - Integrate observability tools (Datadog or equivalent) for real-time performance, drift detection and safety monitoring of AI outputs - Optimize compute and storage architecture to ensure cost-effective scaling of large models and multi-agent workloads - Partner with security, data governance, SRE, and application teams to productize platform capabilities Safety, Security & Compliance Integration - Embed compliance-by-design (HIPAA/CLIA/CAP/FDA/GDPR): PHI/PII handling, encryption, access controls, audit trails - Implement guardrails: input/output filters, prompt hardening, allow/deny policies for tool execution, policy-as-code in CI/CD - Bias/explainability hooks and automated evaluations for RAG/LLM/agents; drift and regression detection Technical Leadership & Mentorship - Establish golden paths (templates, examples, docs) and lead platform architecture reviews, code reviews, and design discussions - Partner with data scientists, AI researchers, and product engineers to deliver reliable and maintainable AI services - Mentor junior engineers in platform development, distributed systems, and agentic AI infrastructure concepts - Influence cross-functional roadmaps by partnering with Product and Engineering leadership to align delivery with business needs Qualifications Required: - 8+ years in software/ML engineering, with 5+ years in ML engineering at scale - Expertise in building production-grade ML/LLM systems on AWS tech stack (Python, TensorFlow/PyTorch, Spark, MLflow/Kubeflow, vector DBs) - Proven track record with GenAI/LLMs: fine-tuning, RAG, prompt orchestration, agentic systems, safety guardrails, monitoring, and cost optimization - Hands-on with RAG systems (embeddings, vector DBs, retrieval policies) and LLM runtime operations (caching, quotas, multi-model routing) - Experience building agentic AI platforms (LangChain, LlamaIndex, CrewAI, Semantic Kernel, or custom) - Deep knowledge of data-intensive systems, distributed architectures, and cloud-native development - Strong grounding in compliance-first engineering in healthcare, biotech, or diagnostics preferred - Track record building secure, compliant data/AI systems and automating policy checks. - Excellent ability to influence across teams, mentor engineers, and set technical standards Preferred: - Masters degree in Computer Science, AI/ML, engineering or related field - Experience in healthcare, pharma, diagnostics, or other regulated industries - Familiarity with AI governance frameworks, bias detection, explainability, and compliance (e.g., HIPAA, CLIA, FDA) The pay range is listed and actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years & depth of experience, certifications and specific office location. This may differ in other locations due to cost of labor considerations. Remote USA $125,000 - $156,300 USD OUR OPPORTUNITY Natera™ is a global leader in cell-free DNA (cfDNA) testing, dedicated to oncology, women’s health, and organ health. Our aim is to make personalized genetic testing and diagnostics part of the standard of care to protect health and enable earlier and more targeted interventions that lead to longer, healthier lives. The Natera team consists of highly dedicated statisticians, geneticists, doctors, laboratory scientists, business professionals, software engineers and many other professionals from world-class institutions, who care deeply for our work and each other. When you join Natera, you’ll work hard and grow quickly. Working alongside the elite of the industry, you’ll be stretched and challenged, and take pride in being part of a company that is changing the landscape of genetic disease management. WHAT WE OFFER Competitive Benefits - Employee benefits include comprehensive medical, dental, vision, life and disability plans for eligible employees and their dependents. Additionally, Natera employees and their immediate families receive free testing in addition to fertility care benefits. Other benefits include pregnancy and baby bonding leave, 401k benefits, commuter benefits and much more. We also offer a generous employee referral program! For more information, visit www.natera.com. Natera is proud to be an Equal Opportunity Employer. We are committed to ensuring a diverse and inclusive workplace environment, and welcome people of different backgrounds, experiences, abilities and perspectives. Inclusive collaboration benefits our employees, our community and our patients, and is critical to our mission of changing the management of disease worldwide. All qualified applicants are encouraged to apply, and will be considered without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, age, veteran status, disability or any other legally protected status. We also consider qualified applicants regardless of criminal histories, consistent with applicable laws. If you are based in California, we encourage you to read this important information for California residents. Link: https://www.natera.com/notice-of-data-collection-california-residents/ Please be advised that Natera will reach out to candidates with a @natera.com email domain ONLY. Email communications from all other domain names are not from Natera or its employees and are fraudulent. Natera does not request interviews via text messages and does not ask for personal information until a candidate has engaged with the company and has spoken to a recruiter and the hiring team. Natera takes cyber crimes seriously, and will collaborate with law enforcement authorities to prosecute any related cyber crimes.
A venture-backed startup building a modern data platform for the real estate industry, enabling automation, analytics, and AI-powered workflows for real estate operators. The team includes engineers and leaders from companies such as major fintech, cloud, and consumer technology platforms, and is focused on solving complex infrastructure and data challenges in a large, underserved industry.
Role Description A fast-growing cloud-native professional services company is hiring Forward Deployed Engineers for a new AI-focused business unit built around enterprise LLM adoption. This is a startup-style team inside a larger, established consulting organization: small team, high autonomy, direct client ownership, and real delivery responsibility from day one. You’ll work directly with enterprise customers to take AI from idea to production. Engagements may focus on AI-assisted software development, agentic engineering workflows, RAG/LLM applications, or applied AI enablement for business teams. - Own client engagements end-to-end: discovery, scoping, architecture, delivery, enablement, and expansion. - Run stakeholder interviews, technical workshops, architecture reviews, and enablement sessions. - Build or guide production AI systems such as agents, RAG pipelines, AI-native apps, workflow automations, or AI-assisted SDLC tooling. - Translate ambiguous business problems into practical, deliverable technical solutions. - Work with both technical and non-technical stakeholders, from engineers and architects to VP/C-suite leaders. - Identify opportunities to expand accounts through strong delivery and proactive problem-solving. - Leave clients with durable capability: documented, maintainable systems, workflows, and enablement materials. Qualifications - 4–10 years of experience in client-facing technical delivery, consulting, systems integration, professional services, FDE, solutions engineering, or customer-facing software engineering. - Hands-on experience with LLM applications, AI agents, RAG pipelines, AI workflows, or AI-assisted development tools. - Comfortable with tools such as Claude, Claude Code, Cursor, Codex, AWS Bedrock, LangChain/LangSmith, Python, AWS, Kubernetes, Zapier, Power Automate, or similar. - Strong consulting instincts: able to run discovery, manage stakeholders, communicate clearly, and drive outcomes without heavy oversight. - Able to speak technically with engineers while also explaining business value to executives. - High tolerance for ambiguity and a bias toward action. Requirements - Two strong-fit profiles: - AI/Workflow Transformation FDE: Consulting, implementation, or enterprise SaaS delivery background with hands-on AI enablement experience. Strong fit for candidates who have helped business teams adopt AI tools, automate workflows, or transform knowledge-worker processes. - Technical / SDLC FDE: Software engineering background with client-facing delivery experience. Strong fit for candidates who have built production AI systems, agentic coding workflows, developer tooling, RAG apps, or engineering enablement programs. - Strong signals: - Prior consulting, professional services, systems integration, or implementation experience. - Experience leading workshops, enablement sessions, or technical discovery. - AWS/cloud consulting background. - Production AI/LLM project experience. - Account expansion or “sell-do” delivery experience. - Comfort working remotely with up to 50% travel depending on client needs.
Founded in 2004 and led by CEO Steve Chapman, Natera is a company in the biotechnology market that offers genetic testing and diagnostics on a global scale. Ope
• Lead the technical design and deployment of multi-agent systems capable of autonomous hypothesis generation and tool use, including genomic variant calling, LLM fine-tuning, and clinical trial matching pipelines • Incorporate and advance Natera’s transformer-based foundation model by integrating DNA, RNA, and H&E imaging modalities for multi-step biological reasoning and tool use • Implement advanced LLM reasoning frameworks, such as ReAct and Chain-of-Thought, alongside reinforcement fine-tuning (RFT) to ensure agents provide accurate, explainable clinical rationales • Architect systems that autonomously translate complex, multi-modal data into diagnostic and therapeutic insights with human-verifiable reasoning and tracing • Own the technical strategy and product roadmap for agentic workflows across the Biopharma Solutions and Therapeutics Discovery division, converting complex clinical challenges into scalable AI systems • Establish production-grade machine learning engineering standards and reproducible architectures across the AI team to ensure absolute model transparency and scientific auditability • Drive cross-functional alignment and technical consensus by defending agentic architectures and biological reasoning frameworks in rigorous peer reviews
• Pipeline Automation: Design, implement, and manage automated CI/CD and Continuous Training (CT) pipelines for machine learning model development, evaluation, and delivery. • Model Deployment: Containerize, deploy, and scale machine learning models as high-availability microservices or batch processing workflows. • Observability & Monitoring: Establish unified logging, alerting, and monitoring solutions to track model inference performance, system latency, resource utilization, data drift, and concept drift. • Infrastructure Management: Provision and optimize cloud-based ML infrastructure (including GPU/CPU computing clusters) utilizing Infrastructure as Code (IaC) paradigms. • Cross-Functional Collaboration: Work intimately with product development teams to drive infrastructure adoption and efficiency gains through SDK/API development, automation and efficient ML system maintenance. • Governance & Compliance: Implement robust lineage tracking for data, code, and model artifacts to ensure compliance, reproducibility, and security across the entire ML lifecycle. • Data Infrastructure & Tooling: Work with data engineering to improve the data ecosystem, ensuring robust, scalable pipelines for experimentation and ML (including streaming tools like Kafka and Flink for low-latency online inference). • Thought Leadership: Act as a mentor and thought leader, helping to define best practices in machine learning engineering, scalable ML service ops, and agentic AI (AI-Native) best practices.
Role Description We are looking for an Application Architect with strong AI engineering experience to design and build intelligent, agentic applications on Google Cloud Platform. This role sits within an application engineering team and focuses on architecting AI-enabled systems using the Google Agentic Development Kit (ADK), Gemini, and Vertex AI — integrated into enterprise Java/Python backends and cloud-native microservices. You are equally comfortable defining application architecture, designing agentic workflows, writing production-quality code, and translating AI capabilities into practical, mission-aligned solutions for federal stakeholders. This role is remote with a preference for candidates located in Virginia, Maryland, or Washington DC. Key Responsibilities - Architect and implement AI-enabled application systems on GCP, with a focus on agentic workflows using Google ADK and Gemini Pro. - Design human-in-the-loop agentic systems — defining agent roles, tool use, orchestration patterns, and guardrails for responsible, auditable AI behavior. - Integrate AI/ML capabilities (Vertex AI, Gemini APIs, embeddings, RAG) into enterprise Java and Python applications via well-designed APIs and microservices. - Lead application-layer design decisions: data flow, context management, session handling, and state management within agentic architectures. - Collaborate with Data Engineers (BigQuery, Dataform) and Cloud Architects to ensure AI application solutions are grounded in reliable, governed data. - Conduct architectural reviews, define coding standards for AI-integrated applications, and mentor engineers on agentic design patterns. - Evaluate AI use cases for feasibility, risk, and mission fit; prototype and validate approaches before committing to full builds. - Contribute to responsible AI practices: explainability, human oversight, auditability, and alignment with federal AI governance requirements. - Stay current on the Google AI ecosystem (Gemini, ADK, Vertex AI Agent Builder) and inform team and leadership on strategic direction. Qualifications - 5–8 years of software or application engineering experience, with demonstrated focus on AI-integrated or intelligent application design. - Hands-on experience with Google ADK or comparable agentic frameworks (LangGraph, LangChain, AutoGen); Google ADK strongly preferred. - Proficiency in Python for AI/ML integration; Java experience a plus in application team context. - Experience integrating LLM APIs (Gemini, OpenAI, or equivalent) into production application workflows. - Solid understanding of agentic design patterns: tool use, multi-agent orchestration, retrieval-augmented generation (RAG), memory and context management. - Experience with GCP services: Vertex AI, Cloud Run, GKE, BigQuery, Pub/Sub. - Familiarity with REST API design, microservices architecture, and CI/CD pipelines (Harness preferred). - Understanding of responsible AI principles: human-in-the-loop design, auditability, bias awareness, and federal AI governance. Desired Qualifications - Experience with Vertex AI Agent Builder, Gemini Code Assist, or Gemini CLI in a development workflow context. - Familiarity with GCP-native data tooling: BigQuery, Dataform, Looker. - Experience on federal or large-scale enterprise modernization programs. - Exposure to FedRAMP/FISMA requirements and security-compliant AI deployment practices. - Experience with DevSecOps pipelines (Checkmarx, Invicti, or equivalent SAST/DAST tooling). Additional Information - Successful completion of a client-required background investigation and suitability determination will be required. - The ability to obtain and maintain a federal security clearance may be required based on engagement. - Bachelor's degree in Computer Science, Software Engineering, or a related field; advanced degree a plus. - Google Cloud Professional Cloud Architect or Professional Machine Learning Engineer certification preferred. - Security+ desirable. Benefits - Health Care Plan (Medical, Dental & Vision) - Retirement Plan (401k, IRA) - Life Insurance (Basic, Voluntary & AD&D) - Paid Time Off (Vacation, Sick & Public Holidays) - Family Leave (Maternity, Paternity) - Short Term & Long Term Disability - Training & Development - Work From Home - Wellness Resources - Employee Bonus Programs
Cohere Health is a Software-as-a-Service (SaaS) company focused on improving the patient journey by enhancing the quality of care at lower costs, as well as emp
Role Description As an intern you will get a front row seat in a fast growing company which will undoubtedly advance your career and give the right candidate an accelerated career path. In this role, you’ll work with our growing team of world-class engineers, statisticians, and clinical experts to develop and deploy machine learning algorithms that help automate burdensome administrative clinical practices. This is a unique opportunity to join a new engineering team with great ambition and building on modern technology with zero legacy technical debt. Last but not least: People who succeed here are empathetic teammates who are candid, kind, caring, and embody our core values and principles. We believe that diverse, inclusive teams make the most impactful work. Cohere is deeply invested in ensuring that we have a supportive, growth-oriented environment that works for everyone. What you will do: - Work on reliable and scalable production machine learning systems - Contribute to feature design, development, testing, and delivery of our machine learning models - Work cross-functionally across diverse stakeholders, including product managers, statisticians, EHR data specialists and physicians - Actively participate in development of machine learning models Qualifications - You are passionate about building quality products and have end-to-end machine learning experience, leading with the right design and development principles - Experience developing in Python, required (NLP/PyTorch experience preferred) - You have familiarity with common software development practices such as version control, unit testing, and CI/CD - You are a team player and are interested in working at a fast-paced startup environment - You are enrolled in a Bachelor’s or higher (MS/PhD) degree program in computer science, machine learning, computational linguistics, statistics, mathematics or similar field - Prior experience in healthcare and life sciences is a plus, but is not required Equal Opportunity Statement Cohere Health is an Equal Opportunity Employer. We are committed to fostering an environment of mutual respect where equal employment opportunities are available to all. To us, it’s personal.
Come join the movement....we are a vehicle to healthy living!
• Partner with the Data Platform team in a two-way exchange of best practices • Adopt common patterns and build effective abstractions across different machine learning pipelines that simplify existing machine learning processes and accelerate the modelling process from the business problem’s inception to deploying a model solution into production • Develop horizontal solutions to robustly scale the team’s machine learning models and processes • Build software with Object-oriented Design Patterns and Analysis (OOA and OOD) with an eye toward reducing technical debt and maintaining services at high availability • Participate in requirements reviews, design reviews, and code reviews • Research and prototype new technologies to support the rapid growth of the business • Interact cross-functionally with a wide variety of technical teams and work closely with data and applied scientists to identify opportunities to improve on iHerb’s platform
ITC Service Group (“ITC”) is an Equal Opportunity Employer. We do not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law.
Role Description We are seeking a Lead AI Engineer to join our Business Operations team. This position may be able to work remotely from anywhere within the United States. The Lead AI Engineer is the first engineering hire on AFL's AI Enablement team, responsible for designing, building, and deploying agentic AI systems that automate the operational backbone of the business through workflow orchestration, model adaptation, and analytics. Working directly with the AI Enablement Manager, the Lead AI Engineer will help lay the technical foundation the rest of the team will build on — including model selection and management, deployment posture, orchestration patterns, evaluation, and audit. As the team grows, an AI Product Manager and AI Operations Specialists will join to take on intake, sequencing, stakeholder coordination, and product ownership of deployed solutions, allowing engineers to stay focused on build work. Responsibilities - Architecture & Technical Foundation: - Establishes the architectural patterns, evaluation practices, and deployment standards for the team. - Makes framework and model recommendations that set the foundation for how the team builds — evaluates orchestration frameworks, selects deployment patterns, trains and fine-tunes models, and determines where managed platforms end and custom build begins. - Solution Design & Delivery: - Translates proposed business solutions into technical plans — defines product life cycles, prioritizes the backlog, and breaks initiatives into buildable work. - Owns solutions end-to-end: technical planning, architecture, build, deploy, and the monitoring that keeps them honest in production. - Production Reliability: - Builds the monitoring, evaluation, and regression detection systems that keep production agents reliable — including logging, performance benchmarking, and feedback loops that surface drift early. - Governance & Collaboration: - Partners with data governance to ensure solutions meet compliance, data quality, and operational standards. Qualifications - Bachelor's degree in Computer Science or related field, or equivalent experience. - 7+ years of software engineering experience with a strong full-stack foundation — backend services, API design, system integration, and data infrastructure. - Recent hands-on experience building AI or LLM-backed systems and shipping them to production. - Experience architecting solutions from scratch and owning them through deployment, observability, testing, and ongoing reliability. - Experience with AI development practices — model selection, fine-tuning, prompt engineering, evaluation frameworks, and understanding when each approach is the right fit. - Proficiency in Python; experience with cloud platforms. - Experience mentoring engineers and setting technical direction across multiple initiatives. - Strong communication skills with both technical and non-technical stakeholders. Working Conditions - Environment: Remote work environment (US-based). - Travel: Occasional travel (domestic) as needed. Benefits - Flexible time off policy. - 401K Company match (up to 4% — dollar for dollar). - Professional development, training, and tuition reimbursement programs. - Excellent medical, dental, vision, and life insurance policy options. - Opportunities for career advancement with an industry-leading company!
Advancing the ways the world pays, banks and invests.
Role Description The Applied AI Engineer - Business Applications will support the optimization of supply chain business processes to improve overall organization performance by developing, maintaining, and testing custom prompt AI models using MS Power Platform. The department focuses on developing and implementing operational excellence strategies that will modernize the Supply Chain organization of the future by improving communication, data synergy, and streamlining processes for automation. The co-op student will be involved in all stages of development, including: - Gathering requirements - Designing - Developing - Testing - Deploying solutions The position will be fully remote, with occasional travel to the office as needed. In-person outings will be organized for the co-op students during the term and attendance is encouraged. The position is available as an 8-month co-op placement. What You Will Be Doing: - Design and optimize prompt-based AI models to improve business process efficiency - Develop low-code solutions using Microsoft Power Platform tools - Integrate AI models into applications to support decision-making and automation - Collaborate with stakeholders to gather requirements and translate them into technical solutions - Build and maintain workflows using Power Automate to streamline operations - Monitor solution performance and implement improvements using data insights - Create clear documentation for applications, workflows, and AI models - Support testing, deployment, and ongoing maintenance of business applications - Apply machine learning APIs to enhance solution capabilities - Stay current with emerging AI, automation, and large language model trends Qualifications - Currently pursuing a degree in computer science, data science, engineering, mathematics, or a related field, or equivalent experience - Hands-on experience with Microsoft Power Platform tools, including Power Apps and Power Automate - Foundational knowledge of AI, machine learning concepts, and prompt engineering - Strong problem-solving and analytical thinking skills - Ability to design and implement data-driven solutions - Experience working with APIs and integrating external services - Effective written and verbal communication skills - Ability to work independently and collaborate within cross-functional teams Preferred Qualifications - Experience with Azure AI or other cloud-based machine learning platforms - Familiarity with data preprocessing, transformation, and integration techniques - Exposure to Power BI for reporting and visualization - Understanding of supply chain processes and operations - Experience working in agile development environments Benefits - Opportunities to make an impact in fintech - Personal and professional learning - Inclusive, diverse work environment - Resources to give back to your community - Competitive salary and benefits
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