Senior AI/ML Engineer
Listed on 2026-02-28
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Software Development
AI Engineer, Machine Learning/ ML Engineer
JOB SUMMARY
The Senior AI/ML Engineer role will design and build custom AI-powered applications end-to-end, from prototype to production, focused on delivering measurable business value. The Senior AI/ML Engineer will engineer full AI systems that integrate model capabilities into real products: robust API endpoints, agentic or AI workflow orchestration, scalable backend services, and well-designed data models. Hands‑on in implementation, deeply involved in system quality and reliability, and eager to mentor junior engineers while raising the team’s engineering bar.
MAJORRESPONSIBILITIES AI Development
- Architect and implement end-to-end AI solutions, including backend services, APIs, databases, and model integration layers.
- Develop and maintain API endpoints (REST/Graph
QL) that reliably serve AI capabilities to internal and external consumers. - Design and implement backend database schemas (relational and/or No
SQL) and data access patterns optimized for AI workloads and application needs. - Build scalable AI infrastructure patterns (job queues, caching, streaming, async workers) to support low-latency and high-throughput use cases.
- Apply secure engineering practices including authentication/authorization, secrets management, threat modeling, and PII handling.
- Implement AI pipelines including Retrieval‑Augmented Generation (RAG), tool/function calling, structured output, and agentic workflows.
- Choose appropriate model strategies: prompt-based, RAG, fine‑tuning, or hybrid approaches based on cost, latency, and quality requirements.
- Evaluate and integrate foundation models (open‑source and commercial) with attention to licensing, security, privacy, and performance.
- Define and implement evaluation frameworks to measure AI system quality (accuracy, relevance, grounding, hallucination rates, safety, latency, cost).
- Create automated test suites for prompts/workflows and regression testing for model and data changes.
- Monitor production systems for drift, degradation, and reliability issues; establish observability (logs, traces, metrics) and incident response practices.
- Partner with Product, Data Science, Data Engineering, Dev Ops and Platform teams to translate requirements into robust technical solutions.
- Mentor junior engineers through code reviews, technical guidance, and best‑practice sharing.
- Lead by example in engineering rigor, craftsmanship, and pragmatic decision‑making.
- Understands and actively participates in Environmental, Health & Safety responsibilities by following established UO policy, procedures, training and team member involvement activities.
- Performs other duties as assigned.
- Bachelor’s degree in computer science, Engineering, Data Science, or a related field is required.
- An advanced degree (Masters or PhD) in a relevant field is strongly preferred, emphasizing computer science, machine learning, robotics, or business management.
- 5+ years in software engineering and/or applied AI/ML roles, with demonstrated delivery of production systems.
- AI/ML Expertise:
Strong working knowledge of modern ML/GenAI tools (e.g., PyTorch/Tensor Flow, Hugging Face, Lang Chain/Llama Index or similar). - Backend Engineering:
Proven ability to build and maintain backend services and APIs (Python/Type Script/Java/Go or similar). - Data & Storage:
Experience designing database schemas and working with relational and/or No
SQL databases; familiarity with vector databases is a plus. - Cloud Proficiency:
Proficient in at least one major cloud provider (AWS, GCP, or Azure), including deployment and managed services. - Evaluation Discipline:
Demonstrated experience measuring AI system quality with repeatable evaluation methods and production monitoring. - Scaling Mindset:
Ability to design systems for performance, reliability, and maintainability at scale. - Communication:
Strong written and verbal communication skills; able to explain tradeoffs clearly to technical and non‑technical stakeholders. - Mentorship:
Eagerness and ability to mentor junior engineers and elevate team practices.
Your talent, skills and experience will be rewarded with a competitive compensation package.
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