Machine Learning Engineer

OCTOPYD; San Francisco (CA); Remote; USD 120,000 - 180,000; Full time

Job summary

A fast-growing AI startup, Octopyd, seeks an ML Engineer to develop intelligent systems revolutionizing hiring through advanced AI. You'll build scalable models, optimize candidate evaluations, and collaborate with experts, all while operating in a flexible, remote-first culture. Bring your machine learning expertise and passion for real-world impact to a team that prioritizes precision and impactful results.

Qualifications

• 5+ years of ML engineering experience.
• 2+ years of LLM hands-on experience.
• Expertise in Python and PyTorch.

Responsibilities

• Fine-tune, evaluate, and deploy LLMs for recruiting.
• Build scalable inference pipelines for AI hiring agents.
• Collaborate with scientists to operationalize models.

Skills

Machine Learning Engineering

Python

PyTorch

LLMs

ML Tooling

Job description

About the Job

Why This Matters

AI is transforming hiring, but most recruiting workflows are still broken, manual, and inefficient. At Octopyd, you’ll be building the intelligent systems that redefine how companies identify, evaluate, and hire top talent. You’ll help develop and scale frontier models that power our multi-agent hiring platform — from AI-driven candidate evaluations to real-time recruiter copilots. If you're excited to bring advanced AI from research into real-world impact, this role is for you.

What You'll Do

• Fine-tune, evaluate, and deploy LLMs and foundation models specialized for recruiting, candidate evaluation, and skill extraction.
• Build scalable inference pipelines, agentic workflows, and retrieval-augmented generation (RAG) systems that power Octopyd’s AI hiring agents.
• Optimize models for latency and throughput via batching, caching, quantization, and streaming to enable fast, interactive candidate assessments.
• Collaborate closely with applied scientists to operationalize experimental models into stable, production-grade features.
• Contribute to architecture design for scalable ML systems across cloud-native infrastructure.
• Own ML features end-to-end — from prototyping to deployment, observability, and continuous improvement in production.

What You Bring

• 5+ years of ML engineering experience delivering production ML systems.
• 2+ years of hands-on experience with LLMs (prompt engineering, fine-tuning, evaluation).
• Deep expertise in Python, PyTorch, and modern ML tooling.
• Familiarity with agentic frameworks (e.g. LangChain, LlamaIndex) and multi-agent AI systems.
• Solid understanding of vector search, semantic embeddings, skill ontologies, and RAG pipelines.
• Strong grasp of scalable ML infrastructure and high-availability inference design.

Bonus Points

• Experience working with applied AI research or in human-in-the-loop AI systems.
• Background in HR tech, recruitment workflows, or ATS integration.
• Startup experience or contributions to fast-paced cross-functional teams.
• Open-source contributions to ML infrastructure or LLM tooling.
• Experience deploying models on cloud platforms (AWS SageMaker, Bedrock, vLLM, SGLang).

What It’s Like Here

Octopyd is a fast-growing AI startup reshaping enterprise recruiting. You'll collaborate directly with engineers, data scientists, and domain experts to ship models that drive real-world hiring outcomes. We move quickly, value precision, and care deeply about building systems that are both elegant and practical. If you're passionate about bringing AI into real operations, you'll thrive here.

Logistics

This position is available remotely within North America. While we value in-person collaboration, we operate with flexibility and a distributed-first culture. Octopyd sponsors work authorization transfers (H1B) for qualified candidates.

How to Apply

Don’t meet every requirement? That’s okay — if you're excited about our mission and believe you can contribute, we encourage you to apply. We're growing quickly and building a world-class team across experience levels.