Senior Machine Learning Engineer

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September 13

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Commit

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Commit is a global tech services company with offices in Israel, US, Canada, UK, and Europe.

501 - 1000 employees

📋 Description

• Integrate and optimize applications using LLM provider APIs (e.g. OpenAI Chat Completions), including model/parameter selection, structured output, function calling, etc. • Design and refine prompts with few-shot, chain-of-thought, context crafting, and prompt chaining techniques. • Benchmark and evaluate models (e.g., reasoning vs. non-reasoning) using custom eval sets and automated testing frameworks. • Build and monitor RAG pipelines, implement summarization, chat with data and other use cases. • Develop robust backend services in .NET and Python, working with SQL, REST APIs, and integrating with LLM services. • Implement LLM tracing, monitoring, and logging for observability. • Apply prompt security best practices, including injection protection and guardrails. • Collaborate across teams to build agentic workflows, and support ETL/data transformations for AI readiness.

🎯 Requirements

• 1-2+ years demonstrable experience in developing Generative AI applications. • 3+ years of experience as a software developer. • Proven hands-on experience with OpenAI APIs, model selection, and LLM capabilities. • Proven hands-on experience with prompt engineering, including structured prompts, function calls, and evaluation techniques. • Experience with RAG and building LLM-centric workflows. • Strong backend development skills in .NET (C#) and SQL. • Proficiency in Python; familiarity with JavaScript. • Experience with Docker, Kubernetes, and RESTful APIs. • Familiarity with Azure, particularly AKS, ACR, and containerized app deployment. • English - fluent speaking, reading and writing. • Advantage: Experience with Azure OpenAI, PromptFlow, Azure AI Services, and Azure ML. • Advantage: Familiarity with CosmosDB, KQL, Azure Log Analytics, App Insights. • Advantage: Exposure to other LLM APIs (Anthropic, Mistral, Cohere, etc.). • Advantage: Prompt caching/compression, LLM output validation. • Advantage: Familiarity with Redis caching. • Advantage: Frontend experience with React and Next.js.