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.