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Senior Meta Machine Learning Jobs in Minnesota (NOW HIRING)

3M

Senior Manager - Data Engineering

Maplewood, MN · On-site

Senior Manager - Data Product Engineering Collaborate with Innovative 3Mers Around the World ... Ensuring data products are designed to support AI applications , machine learning, intelligent ...

3M

Senior Manager - Data Engineering

Maplewood, MN · On-site

Senior Manager - Data Product Engineering Collaborate with Innovative 3Mers Around the World ... Ensuring data products are designed to support AI applications , machine learning, intelligent ...

Vizient, Inc.

Senior Software Engineer

Edina, MN · On-site

$102K - $179K/yr

You will collaborate with AI/ML engineers, data scientists, product teams, and clients to deploy machine learning models, LLM applications, and intelligent automation solutions into production. You ...

Vizient, Inc.

Senior Software Engineer

Edina, MN · On-site

$102K - $179K/yr

You will collaborate with AI/ML engineers, data scientists, product teams, and clients to deploy machine learning models, LLM applications, and intelligent automation solutions into production. You ...

Vizient, Inc.

Senior Software Engineer

Edina, MN

$102K - $179K/yr

You will collaborate with AI/ML engineers, data scientists, product teams, and clients to deploy machine learning models, LLM applications, and intelligent automation solutions into production. You ...

Vizient, Inc.

Senior Software Engineer

Edina, MN · On-site

$102K - $179K/yr

You will collaborate with AI/ML engineers, data scientists, product teams, and clients to deploy machine learning models, LLM applications, and intelligent automation solutions into production. You ...

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Senior Meta Machine Learning information

What is the difference between Senior Meta Machine Learning vs Data Scientist?

AspectSenior Meta Machine LearningData Scientist
Required CredentialsMaster's or PhD in CS, ML, or related fields; experience with meta-learning frameworksBachelor's or higher in CS, Statistics, or related fields; proficiency in data analysis
Work EnvironmentResearch-focused teams developing advanced ML models, often in AI companiesData analysis, modeling, and visualization across various industries
Employer & Industry UsageTech firms, AI startups, research institutionsFinance, healthcare, e-commerce, tech companies

While both roles involve machine learning expertise, Senior Meta Machine Learning specialists focus on developing advanced meta-learning algorithms, often in research settings, whereas Data Scientists apply data analysis and modeling techniques across diverse industries. The roles share similar educational backgrounds but differ in focus and application.

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The most popular types of Meta Machine Learning jobs in Minnesota are:

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Senior Meta Machine Learning jobs near you

Senior Consultant, AI/ML Ops Engineer

Horizontal Talent

Minneapolis, MN • On-site, Remote

$109K - $149K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Join a senior-level AI and machine learning engineering role focused on building production-ready models, GenAI applications, and the shared platform that supports them. This opportunity is ideal for an experienced engineer who enjoys moving between applied data science, AI product development, and platform engineering to help bring impactful solutions from prototype to production.

Responsibilities
  • Develop and evaluate machine learning models for use cases such as ranking, scoring, forecasting, classification, and survival or time-to-event analysis.
  • Apply strong experimental methods to validate models, assess performance, and review subgroup behavior, calibration, and potential failure modes.
  • Combine model outputs with business logic and domain rules to support clear, trustworthy recommendations.
  • Design and deliver GenAI-enabled applications, including RAG workflows, agents, structured extraction, summarization, and reasoning trails.
  • Build and improve evaluation frameworks for model and prompt changes, including offline and online testing, regression checks, and quality safeguards.
  • Extend and support shared AI platform capabilities such as model access, routing, budget controls, failover, and observability.
  • Own retrieval and grounding components, including embeddings, vector storage, chunking strategies, and retrieval quality tuning.
  • Productionize AI services using modern Python development practices, containers, AWS services, and CI/CD workflows.
  • Monitor deployed solutions for performance, latency, reliability, cost, drift, and overall quality.
  • Partner with data scientists, MLOps professionals, domain experts, and product stakeholders to move solutions into production.
  • Provide technical leadership through design reviews, code reviews, mentoring, and the creation of reusable engineering patterns.
Skills
  • 5+ years of experience building and shipping ML or AI solutions in production environments.
  • Strong foundation in machine learning concepts, feature engineering, model evaluation, and experimental design.
  • Experience with ranking, scoring, or survival/time-to-event modeling.
  • Hands-on experience with GenAI and LLM application development, including RAG, prompt engineering, function or tool calling, embeddings, and vector search.
  • Advanced Python development skills with an emphasis on clean, maintainable, and testable code.
  • Experience building APIs, services, or shared libraries for production use.
  • Experience working with AWS services such as Bedrock, SageMaker, Lambda, and S3.
  • Knowledge of Docker and Git-based development workflows.
  • Understanding of software engineering best practices, including testing, code review, version control, and CI/CD.
  • Ability to think through cost, latency, and reliability considerations for AI systems.
  • Strong communication and collaboration skills with the ability to work across technical and non-technical partners.
Preferred Skills
  • Experience building AI platform components such as gateways, routing layers, multi-tenant tooling, or internal SDKs.
  • Familiarity with agent frameworks, real-time or voice AI, or streaming inference.
  • Experience with vector databases such as Qdrant, OpenSearch, or pgvector.
  • Exposure to infrastructure as code, observability tools, and cloud monitoring practices.
  • Experience supporting AI workloads with operational cost management and optimization practices.
  • Background in healthcare, clinical, or other regulated environments with attention to data governance and auditability.
  • Experience serving models as endpoints and supporting train/serve parity.
  • Comfort working with sensitive data in a governed environment.

Horizontal is committed to fostering an inclusive, respectful, and equitable workplace where different perspectives and experiences are valued. We encourage candidates from all backgrounds to apply and bring their unique strengths to the team.

By applying for this position, you acknowledge and agree that Horizontal Talent may contact you regarding your application using automated technology, including phone calls, SMS/text messages, or email, which may be delivered by our virtual AI recruiter, Alex.

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