Machine Learning Engineer Remote Jobs in Minnesota (US)
This page tracks remote machine learning engineer openings that are location-eligible for Minnesota.
This page tracks remote machine learning engineer openings that are location-eligible for Minnesota.
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• Deliver phase-one AI capabilities in our existing Amazon Connect environment, focusing on AI-first call handling, intelligent routing, and autonomous resolution of common login, account, and password-reset queries. • Design AI-first workflows for voice and email that prioritize autonomous resolution, allowing the system to intelligently decide when to handle a request end-to-end and when to route to an agent. • Leverage our existing call recordings and transcripts to extract real interaction patterns and customer language to ground the AI in actual member needs. • Build elegant handoff patterns that preserve a member's interaction history, intent, and attempted actions so they never have to repeat themselves. • Write clean, production-ready Python backend code and AWS Lambda integrations to handle secure account lookups, validation, and CRM updates. • Integrate Amazon Connect workflows with HubSpot and other internal systems to equip the AI agent with real-time customer context. • Establish a reusable metadata and session strategy to enrich ongoing and future interactions with purchase history and communication logs. • Tune RAG (Retrieval-Augmented Generation) patterns and Bedrock Knowledge Bases to keep AI responses grounded in approved policies and procedures. • Implement practical guardrails that keep AI responses focused on approved topics and apply secure verification steps for sensitive workflows. • Deploy and manage AWS resources using CloudFormation, CDK, or Terraform, ensuring version-controlled deployments of Connect flow JSONs. • Author clean, clear architecture runbooks, deployment procedures, and prompt configurations to ensure the wider team can easily operate your work. • Lay the technical foundations for future authenticated transactions like billing updates, self-service cancellations, and payment processing.
Self-described as "a new company with an old-fashioned goal," Aledade aims to put healthcare control back into the hands of doctors. Headquartered in Bethesda,
Location: Staff AI Researcher Workplace: remote Category: Engineering Job Description: Job Duties/Description: The Staff AI Researcher is responsible for developing advanced artificial intelligence solutions that improve health outcomes for millions of patients by empowering primary care physicians with technology that keeps patients healthy and prevents unnecessary hospitalizations. The Staff AI Researcher collaborates with engineering and analytics teams to bring AI technologies into existing products and workflows. Additionally, the role involves training, fine-tuning, and using AI models harnessing knowledge from extensive data sets of medical records, diagnoses, claims, and prescriptions collected from millions of patients across the country. Primary duties include building working prototypes using off-the-shelf and novel AI techniques to deliver higher levels of optimization for the company; working with large, complex data sets and solving difficult, non-routine analytical problems to harvest data; redesigning existing pipelines and systems to meet growing data and query needs; implementing techniques for fine-tuning and adapting pre-trained generative models to specific healthcare domains or tasks; developing evaluation metrics and benchmarks to assess the quality and performance of AI/ML models; designing and implementing feature engineering pipelines, including data processing, feature extraction, and transformation to optimize model performance; setting and upholding standards for engineering processes, including style and code checking, test harnesses, and release packaging; and delivering working proof-of-concept solutions that balance speed, scalability, and time-to-market considerations. This is a remote work position. Multiple positions are available. Minimum Requirements Must have a Master’s degree or foreign degree equivalent in Computer Science or a related quantitative field and six (6) years of machine learning and statistical analysis experience. The position also requires demonstrated knowledge and experience with the following: three (3) years of deep learning and large language model experience; three (3) years of Python experience; three (3) years of proficiency in selecting the right tools given a data optimization problem; addressing challenges from incomplete, unrepresentative, and mislabeled data; and large-scale distributed systems at scale and statistical software (e.g., Spark). This is a remote work position. Who We Are: Aledade, a public benefit corporation, exists to empower the most transformational part of our health care landscape - independent primary care. We were founded in 2014, and since then, we've become the largest network of independent primary care in the country - helping practices, health centers and clinics deliver better care to their patients and thrive in value-based care. Additionally, by creating value-based contracts across a wide variety of health plans, we aim to flip the script on the traditional fee-for-service model. Our work strengthens continuity of care, aligns incentives and ensures primary care physicians are paid for what they do best - keeping patients healthy. If you want to help create a health care system that is good for patients, good for practices and good for society - and if you're eager to join a collaborative, inclusive and remote-first culture - you've come to the right place. What Does This Mean for You? At Aledade, you will be part of a creative culture that is driven by a passion for tackling complex issues with respect, open-mindedness and a desire to learn. You will collaborate with team members who bring a wide range of experiences, interests, backgrounds, beliefs and achievements to their work - and who are all united by a shared passion for public health and a commitment to the Aledade mission. In addition to time off to support work-life balance and enjoyment, we offer the following comprehensive benefits package designed for the overall well-being of our team members: - Flexible work schedules and the ability to work remotely are available for many roles - Health, dental and vision insurance paid up to 80% for employees, dependents and domestic partners - Robust time-off plan (21 days of PTO in your first year) - Two paid volunteer days and 11 paid holidays - 12 weeks paid parental leave for all new parents - Six weeks paid sabbatical after six years of service - Educational Assistant Program and Clinical Employee Reimbursement Program - 401(k) with up to 4% match - Stock options - And much more! At Aledade, we don’t just accept differences, we celebrate them! We strive to attract, develop and retain highly qualified individuals representing the diverse communities where we live and work. Aledade is committed to creating a diverse environment and is proud to be an equal opportunity employer. Employment policies and decisions at Aledade are based on merit, qualifications, performance and business needs. All qualified candidates will receive consideration for employment without regard to age, race, color, national origin, gender (including pregnancy, childbirth or medical conditions related to pregnancy or childbirth), gender identity or expression, religion, physical or mental disability, medical condition, legally protected genetic information, marital status, veteran status, or sexual orientation. Privacy Policy: By applying for this job, you agree to Aledade's Applicant Privacy Policy available at https://www.aledade.com/privacy-policy-applicants
Role Description The Machine Learning Engineer will work in close collaboration with the core instrument, assay and software teams to develop algorithms for data analysis and workflow automation. This role reports to the Sr. Director AI and can be based in our San Diego CA or Foster City CA offices, or remotely (if candidate not located within commutable distance of either office). - Design, develop, and optimize advanced algorithms for workflow automation, which include computer vision and computational geometry components. - Develop signal-processing and image-analysis algorithms using classical methods as well as modern AI/ML approaches, including neural networks. - Perform system-level analysis, simulation, and validation to ensure algorithm performance meets product requirements. - Collaborate with cross-functional hardware, software, and product engineering teams to integrate algorithms into our broader software ecosystem. - Optimize algorithms for deployment on edge devices, GPUs, and high-performance computing environments with considerations for latency, throughput, and memory efficiency. - Create technical documentation, validation reports, and performance metrics to support product development and cross-team collaboration. Qualifications - Typically requires a Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, Applied Mathematics, Physics, or a related technical field with 5+ years of relevant experience, or a Master’s degree with 3+ years of relevant experience. - Experience developing, implementing, and validating algorithms for optimization, automation, sensing, data analysis, or image-processing applications. - Strong programming skills in Python with experience developing production-quality, maintainable, and well-documented code. - Solid understanding of software development fundamentals, including debugging, version control, testing, and code optimization. - Familiarity with AI/ML concepts and workflows, including data preprocessing, model training, evaluation, and deployment. - Experience with image analysis, computer vision, signal processing, or data-driven algorithm development. - Understanding of mathematical foundations relevant to algorithm development, including linear algebra, probability/statistics, optimization methods, and estimation theory. - Experience applying algorithmic techniques such as optimization, dynamic programming, numerical methods, or statistical modeling to solve engineering problems. - Familiarity with workflow automation, process optimization, or development of efficient data-processing pipelines. - Ability to analyze complex technical problems, evaluate tradeoffs, and develop scalable algorithmic solutions. - Excellent communication skills and ability to work independently and collaboratively in a multidisciplinary team environment. Requirements - Proficiency in C++, C#, or other high-performance programming languages for algorithm deployment and system integration. - Experience developing AI/ML algorithms for image analysis, pattern recognition, anomaly detection, or automated decision systems. - Advanced familiarity with modern computer vision and deep learning architectures, including Vision Transformers (ViTs), CNNs, object detection, segmentation, or multimodal AI models. - Experience with machine learning frameworks such as PyTorch, TensorFlow, or similar platforms. - Experience optimizing algorithms for performance, scalability, memory efficiency, or real-time execution. - Familiarity with optimization and estimation techniques such as convex optimization, Kalman filtering, Bayesian estimation, nonlinear optimization, or stochastic methods. Benefits - Competitive total compensation packages, including base pay, benefits, and equity. - Estimated base salary range for this position in California is $160,000 - $215,000/year. - Comprehensive employment package that includes a competitive salary, generous stock options, great individual and family health plans, a 401(k), and flexibility to balance work and life.
• Build scalable pre-training pipelines for foundation models, optimizing throughput and efficiency. • Implement distributed training strategies across GPUs/TPUs and high-performance clusters. • Collaborate with researchers to translate experimental setups into production-ready workflows. • Develop monitoring and fault-tolerance systems to ensure reliable large-scale training. • Continuously benchmark and tune performance across hardware and software stacks.
Data Science, Digital Transformation and eCommerce Strategy from experienced eCommerce and AI/ML experts
Role Description We are looking for an exceptional AI Architect to design, build, and optimize AI-driven applications on the Azure platform. This role emphasizes strong engineering expertise, creative problem-solving, and the ability to work with cutting-edge technologies to deliver high-impact solutions. The ideal candidate thrives on solving complex challenges, is passionate about engineering excellence, and has a knack for integrating AI into scalable, real-world applications. A background in data science or formal engineering is a strong advantage, given the scientific nature of the work. Key Responsibilities - Architect & Build: Design and implement AI applications leveraging Azure services (AKS, Azure Container Apps, Blob Storage, Document Intelligence, AI Studio/Foundry, VNETs). - Full-Stack Development: Develop systems using C#, Python, React, and modern frameworks like Entity Framework Core, LangChain, Semantic Kernel, and FastAPI. - Scalable & Secure Solutions: Create applications that are resilient, secure, and optimized for high performance. - Collaboration: Work closely with cross-functional teams, including data scientists and engineers, to turn abstract ideas into functional solutions. - Cloud-Native Focus: Lead the deployment and optimization of applications in Azure environments with strong consideration for cost efficiency and maintainability. - Innovate & Optimize: Explore new tools, frameworks, and methodologies to stay at the forefront of AI and software engineering. Qualifications - Proven expertise in software engineering with experience in C#, Python, and React (TypeScript). - Hands-on experience with cloud platforms, particularly Azure, including services like AKS, Networking, and AI Studio/Foundry. - Familiarity with AI frameworks like LangChain, Semantic Kernel, and other AI libraries or tools, as well as techniques such as RAG, Agentic patterns, and workflow orchestration. - Strong grasp of modern development practices, such as containerization, CI/CD, and API design. - Demonstrated ability to design and build secure, scalable, and maintainable systems. Preferred Skills - Background in data science or formal training in engineering disciplines. - Experience with frameworks like Entity Framework Core, Material UI, and FastAPI. - Understanding of AI modeling workflows and integration of document intelligence or related tools. Core Qualities - Problem-Solving Excellence: A creative and analytical approach to tackling technical challenges. - Ownership & Accountability: Ability to take full responsibility for the design, implementation, and success of projects. - Adaptability: Comfortable learning and implementing new technologies in a fast-evolving field. - Team Collaboration: Strong communication skills and a mindset that thrives in a team-driven environment. Company Description Nimble Gravity is a team of outdoor enthusiasts, adrenaline seekers, and experienced growth hackers. We love solving hard problems and believe the right data can transform and propel growth for any organization. Nimble Gravity is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics or any other basis forbidden under federal, state, or local law. Nimble Gravity considers all qualified applicants.
Based in Austin, Texas, Osano is a software company that helps organizations maintain compliance with laws in 40 countries, doing so through its easy-to-use data privacy platform.
Role Description We’re looking for a Senior AI Engineer to join our Engineering team. This person will play a pivotal role in architecting and delivering privacy-first AI systems that power the next generation of Osano’s product capabilities. This role goes beyond wrapping APIs or building chat interfaces. You will: - Design and deploy autonomous AI agents - Develop strict-source-following RAG systems - Implement evaluation frameworks that ensure reliability, compliance, and production-grade performance This position is ideal for someone who is highly technical, thrives in ambiguity, takes ownership of 0→1 initiatives, and believes responsible AI development is non-negotiable. Responsibilities - AI System Architecture - Architect and deploy autonomous AI agents and multi-agent workflows - Design strict-source-following Retrieval-Augmented Generation (RAG) systems that minimize hallucination and enforce citation integrity - Implement guardrails, structured outputs, and validation layers - Production Engineering - Build scalable backend services using FastAPI - Orchestrate agentic workflows using LangGraph - Deploy and manage AI workloads within AWS or Azure - Optimize model performance, reliability, and cost - Evaluation & Continuous Improvement - Develop rigorous evaluation pipelines measuring: - Accuracy - Citation adherence - Latency - Reliability - Establish metric-driven iteration cycles - Continuously refine deployed systems based on measurable outcomes - Privacy-First Development - Embed privacy-by-design principles across the AI stack - Ensure compliance, data sovereignty, and secure handling practices - Collaborate cross-functionally to align AI capabilities with regulatory standards Qualifications - 5+ years of professional experience - Experience deploying and managing AI workloads in AWS or Azure - Deep technical understanding of LLM usage and orchestration beyond prompt engineering - Strong expertise in Python AI ecosystem, specifically: - FastAPI - LangGraph - Proven experience building: - Complex RAG systems - Autonomous AI agents - Experience building evaluation frameworks and iterating based on performance metrics Requirements - Experience with Knowledge Graphs to enhance RAG precision - Familiarity with Privacy-Enhancing Technologies (PETs) - Experience with data anonymization techniques - Background in compliance-heavy or regulated environments Benefits - Competitive-pay compensation and ownership interest/equity - Unlimited paid time off, plus a requirement to take at least two weeks off per year - We're a Best Place for Working Parents and offer paid parental leave for all new parents - Osano sponsors individual premiums on base plans at 100% and dependent premiums at 50% for Medical, Dental, and Vision insurance via Aetna - A fully and permanently remote company, so you can work from anywhere in the U.S. - Receive a MacBook and $600 to craft your home workspace - Annual company trip designed to foster connection, creativity, and fun - Mental health benefits with free memberships to mindfulness and talk therapy services
We're unlocking the power of data to help create a better tomorrow.
• Build scalable, production-grade AI systems that automate and enhance credit analytics and credit decisioning workflows • Develop and integrate AI solutions across the credit lifecycle, including origination, underwriting, limit setting, portfolio monitoring, and model validation • Develop evaluation and guardrail frameworks to ensure response accuracy, reduce hallucinations, and support human-in-the-loop review, including offline testing with ground-truth datasets • Develop and operate enterprise-grade AI services with a focus on scalability, security, reliability, performance, and latency optimization • Implement LLMOps and GenAI operational practices, including prompt management, model versioning, monitoring, CI/CD pipelines, and observability for cost, latency, and response quality • Partner with analytics, engineering, and product teams to embed AI into existing platforms and deliver new AI-driven capabilities across the organization • Evaluate and adopt modern orchestration frameworks and cloud-native AI tools (such as LangGraph and AWS-based services), while staying current with new AI system design patterns
• 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
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• Define and drive the vision, strategy, and roadmap for enterprise semantic data and data connectivity across business domains • Partner with business and IT leaders to identify high-value opportunities to connect and standardize data across systems • Position the semantic data product as a product, not just a technical asset, with clear customers, outcomes, adoption goals, and success metrics • Define and evolve the product’s value proposition, ensuring alignment to business priorities and measurable outcomes • Act as the general manager of the product, balancing user needs, technical feasibility, strategic priorities, operational constraints, and business impact • Define and manage data products aligned to key business domains, including clear ownership, users, and success metrics • Define target users and use cases for data products, ensuring alignment to specific decisions, workflows, and business outcomes • Partner closely with business customers to ensure data products support critical decisions, workflows, and operational outcomes • Drive adoption and usage of shared data assets across business units • Identify and prioritize use cases where connected data unlocks measurable business value (e.g., improved decisioning, automation, personalization) • Ensure solutions are aligned to real-world workflows and deliver tangible outcomes • Lead the development and evolution of enterprise ontologies, taxonomies, and data models that represent key business concepts and relationships • Establish a scalable semantic layer that enables reuse across analytics, AI, and operational use cases • Ensure alignment of definitions across domains to reduce fragmentation and duplication • Support both structured and unstructured data integration, enabling downstream AI and analytics applications • Ensure data is discoverable, understandable, and usable across teams through consistent definitions and relationships • Partner deeply with business domains to understand workflows, decision points, and data dependencies, acting as a product owner for how data supports those functions • Own the end-to-end product lifecycle from discovery and definition to delivery and iteration • Define product requirements, success metrics, and release plans • Continuously refine the semantic data product based on user feedback and evolving business needs • Define critical metrics to measure adoption, usability, and impact of the semantic data product • Supervise usage and continuously improve accessibility and value delivery • Evangelize the value of connected semantic data across the organization • Partner with data governance teams to establish standards, definitions, and data quality expectations • Promote consistency, reusability, and scalability of data assets across the enterprise
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• Diagnose business problems before building solutions • Own AI initiatives end-to-end, from stakeholder discovery and technical design through implementation, deployment, and iteration • Design, develop, and ship AI-powered solutions quickly • Improve organizational flow by building solutions that reduce bottlenecks, shorten lead times, and increase throughput • Integrate AI capabilities into existing systems and workflows using APIs, orchestration tools, and modern AI platforms • Be Customer Zero: leverage and showcase GitLab's AI offerings wherever possible • Partner closely with stakeholders across functions to understand the real constraints • Define and track success through business metrics, flow metrics, and feedback loops that make performance visible and actionable • Contribute to technical direction by evaluating tools, documenting patterns, and creating reusable foundations
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Python, AWS, Distributed Systems, Cloud, JavaScript, DynamoDB