Job description

Highlight is building a shared intelligence layer for the modern workforce. Highlight unifies context across every person and tool on your team, seamlessly bridging information silos. It evolves with your organization to proactively route knowledge and reliably automate workflows. The Role We're hiring a Member of Technical Staff to help build the AI systems that power Highlight. You will work across the full ML stack: data pipelines, model training, retrieval, ranking, evals, and deployment. You will ship features that make Highlight feel like magic. This is a hands on IC role where you will own critical systems end to end and collaborate closely with our Head of AI Engineering to scale our ML capabilities. You will thrive here if you love shipping production ML systems, obsess over output quality, and want to work on hard problems with real user impact. We move fast, hold a high bar, and believe the best ideas win regardless of title. Note: this is an on site role, requiring five days a week in our office. Job Responsibilities - Design, build, and optimize ML pipelines for context retrieval, action detection, and output generation - Implement and iterate on RAG systems, ranking models, and prompt engineering to improve quality - Build comprehensive evals and monitoring to measure and improve ML system performance - Investigate alternative models and fine tuning approaches for our heavy background processing workloads, implementing better systems to increase quality while improving cost efficiency - Collaborate with Backend and Product Engineering to ship AI powered features - Contribute to ML infrastructure decisions and best practices across the engineering org - Stay current on LLM advances, retrieval techniques, and ML tooling; bring insights back to the team Profile We’re looking for someone who is interested in building the AI user experience for the future. We punch above our weight so we value extreme ownership, accountability, and proactiveness. The ideal candidate is a master craftsman who enjoys building great products with LLMs at scale. You are a good fit if you have: - 4+ years in ML/AI engineering, with significant experience shipping production systems - Strong software engineering fundamentals: you write clean, maintainable code - Deep experience with retrieval, ranking, RAG, or search systems at scale - Hands on proficiency with PyTorch, vector databases, and modern ML infrastructure - Experience with LLM applications (prompt engineering, fine tuning, eval frameworks) - Product thinker: understands how to connect great ML products to constraints, evals, and modeling when building them - A bias toward action: you ship fast, measure rigorously, and iterate based on data - Ownership mentality (no task is too small for you) – it’s all hands on deck here and we need everyone rowing the boat. - Excellent communication skills and a collaborative mindset – we’re extremely lean so we’re looking for a team player who works well with others. - Type-A tendencies: maybe you’re extremely detail-oriented. Or maybe you take pride in shipping high-quality products. Whatever it is you do, you give it your all. - Must be based in or willing to relocate to SF – although we’re flexible with days off & schedules, we have a 100% in-office culture during the week. And even if you don’t fall neatly into any of these buckets, we’re looking for scrappy and motivated self-starters above all. Hustle is expected, grit is required. Perks - Competitive salary and generous equity package - Health, dental, and vision insurance - Flexible PTO and parental leave - Paid team lunches during the week - Relocation package

Requirements

Must-haves

Note: this is an on site role, requiring five days a week in our office.
Design, build, and optimize ML pipelines for context retrieval, action detection, and output generation
Implement and iterate on RAG systems, ranking models, and prompt engineering to improve quality
Build comprehensive evals and monitoring to measure and improve ML system performance
Investigate alternative models and fine tuning approaches for our heavy background processing workloads, implementing better systems to increase quality while improving cost efficiency
Collaborate with Backend and Product Engineering to ship AI powered features
Contribute to ML infrastructure decisions and best practices across the engineering org
Stay current on LLM advances, retrieval techniques, and ML tooling; bring insights back to the team
You are a good fit if you have:
4+ years in ML/AI engineering, with significant experience shipping production systems
Strong software engineering fundamentals: you write clean, maintainable code
Deep experience with retrieval, ranking, RAG, or search systems at scale
Hands on proficiency with PyTorch, vector databases, and modern ML infrastructure
Experience with LLM applications (prompt engineering, fine tuning, eval frameworks)
Product thinker: understands how to connect great ML products to constraints, evals, and modeling when building them
A bias toward action: you ship fast, measure rigorously, and iterate based on data
Ownership mentality (no task is too small for you) – it’s all hands on deck here and we need everyone rowing the boat.
Excellent communication skills and a collaborative mindset – we’re extremely lean so we’re looking for a team player who works well with others.
Type-A tendencies: maybe you’re extremely detail-oriented. Or maybe you take pride in shipping high-quality products. Whatever it is you do, you give it your all.
Must be based in or willing to relocate to SF – although we’re flexible with days off & schedules, we have a 100% in-office culture during the week.
And even if you don’t fall neatly into any of these buckets, we’re looking for scrappy and motivated self-starters above all. Hustle is expected, grit is required.

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

aimlllm

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

Pto

Parental Leave