Responsible for design and development of production-grade Machine Learning ops and Gen AI solutions
Lead hands-on delivery of scalable GenAI solutions from problem framing → prototyping → evaluation → production → monitoring.
Build internal copilots/assistants (knowledge search, code/content generation) and client-facing products (conversational analytics, summarization, recommendations, workflow automation).
Design RAG pipelines, embedding strategies, vector search, and model orchestration; evaluate fine-tuning vs. prompt engineering.
Implement guardrails, safety filters, prompt/version management, latency/throughput optimizations, and cost controls.
Identify areas that require improvements or additional functionalities and use your expertise in machine learning and software engineering to architect and develop solutions that fill gaps in our ML platform and development ecosystem.
Analyze system performance, scalability, and reliability to pinpoint opportunities for enhancement.
Optimize the scalability, performance, and reliability of AI Team solutions by implementing best practices and leveraging industry-standard technologies.
Collaborate with infrastructure teams to ensure smooth integration and deployment of ML solutions.
Streamline data ingestion, preprocessing, feature engineering, and model training workflows to improve efficiency and reduce latency.
Evaluate and optimize model prototypes for real-world performance and integrate ML models into production systems with partner teams to communicate and understand technical requirements and challenges.

Requirements

5+ years building production software/ML systems, including 1+ years of experience with LLMs/GenAI.
Proficient in Python and one major DL/LLM stack (e.g., PyTorch/Transformers); experience with LangChain/LlamaIndex, vector DBs, and cloud (AWS/Azure/GCP).
Demonstrated delivery of RAG, prompt engineering, evaluation frameworks, and guardrails in production.
Strength in APIs, distributed systems, and ML Ops (K8s, CI/CD, monitoring).
Experience with EPIC health platform is highly preferred
Experience with ML platforms and ML Ops: Demonstrated experience in assessing and improving ML platforms, identifying gaps, and architecting solutions to address them. Strong familiarity with ML platform components such as data ingestion, preprocessing, feature stores, model training, deployment, and monitoring.
Experience with SQL and big data platforms such as Postgres, Redshift and Snowflake
Experience with Agile/Scrum methodology and best practices
Understanding of use and implementation of Vector Databases
Kubernetes container orchestration experience

Benefits

Medical, Dental, Vision plans
Adoption, Fertility and Surrogacy Reimbursement up to $10,000
Paid Time Off and Sick Leave
Paid Parental & Family Caregiver Leave
Emergency Backup Care
Long-Term, Short-Term Disability, and Critical Illness plans
Life Insurance
401k/403B with Employer Match
Tuition Assistance – $5,250/year and discounted educational opportunities through Guild Education
Student Debt Pay Down – $10,000
Reimbursement for certifications and free access to complete CEUs and professional development
Pet Insurance
Legal Resources Plan
Colleagues have the opportunity to earn an annual discretionary bonus if established system and employee eligibility criteria is met.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Machine LearningGen AIPythonDeep LearningLLMsRAG pipelinesprompt engineeringAPIsKubernetesSQL

Soft Skills

leadershipcollaborationproblem framingcommunicationanalytical thinkingcreativityadaptabilityattention to detailorganizational skillscritical thinking