Senior Machine Learning Engineer

Job Description:

Our Technology team drives the evolution of our Technology, Engineering, Data, Product and User Experience functions. With a keen focus on delivering cutting-edge solutions, we shape the digital landscape for our customers, readers and users. From revolutionizing visuals to optimizing tools and harnessing the power of data, mobile, video and social platforms, our team is committed to providing a seamless and immersive experience across all touchpoints. Collaborating closely with our newsrooms and strategic partners, we spearhead the development of groundbreaking products and technologies.

As Senior Machine Learning Engineer in the AI & ML foundations team, you will design and build the core systems behind our LLM applications: the orchestration layer, the reusable tooling and the evaluation harness that keeps it trustworthy in production. In this role, you will not be applying AI research or model training - but to real problems in production. You will report to the Director, Data Science & Insights.

• Design and build the orchestration, prompting, and workflow layers behind production AI features

• Create composable tools and integrations, including retrieval and MCP servers and clients

• Build evaluators, dashboards, and alerts that track accuracy, latency, cost, and hallucination

• Harden the platform for production scale: caching, reliability, incidents, and model rollbacks

• Set the technical bar through architecture decisions, design reviews, and mentoring

• At least 2+ years’ experience in software/ML engineering - which includes at least 1 years’ experience building LLM systems in production

• Expert Python, hands on with LLM APIs and cloud platforms (AWS, Snowflake, Vertex)

• Deep experience orchestrating multistep LLM workflows as execution graphs (e.g. LangChain/LangGraph).

• Experience building agent harnesses: memory compression, skill disclosure, and tool design

• Strong prompt engineering: tuning, versioning, and evaluation of prompts and model configs

• A proven track record in AI evaluation, observability, and retrieval over enterprise data

• Ability to explain complex AI concepts and tradeoffs clearly to nontechnical stakeholders

• Fluency with agentic coding tools (e.g. Claude Code) and their architecture patterns (a strong plus)