Machine Learning Engineer

About Clay

Clay is a creative tool for growth. Our mission is to help businesses grow  — without huge investments in tooling or manual labor. We’re already helping over 100,000 people grow their business with Clay. From local pizza shops to enterprises like Anthropic and Notion, our tool lets you instantly translate any idea that you have for growing your company into reality. We’re looking for sharp, low-ego people to help us turn every business’s creative ideas into a reality.  Check out our wall of love to learn more about the product.

Why is Clay the best place to work in New York?

• Customers love the product (100K+ users and growing)

• We’re growing a lot (10x YoY for the past two years) 

• Incredible culture (our customers keep applying to work here)

• In-person work (beautiful office space in Flatiron)

• Well-resourced (raised a Series B in June 2024 from investors like Sequoia and Meritech)

Machine Learning Engineer @ Clay

The AI team at Clay is responsible for Claygent – an agentic web researcher – and ML-powered flows within the product. As a Machine Learning Engineer on the AI team, you will own the direction of these ML-powered features and build the underlying models. Product at Clay is federated across Engineering and Design so you have the opportunity to imagine how ML can transform the GTM industry.

What You’ll Do

• Identify opportunities for where ML can fit into the product and work with design to bring those visions to life

• Prototype and productionize the models that power these ML experiences

• Collaborate with the Product Engineering team to integrate the models into the product (or if you’re interested in full stack engineering work you can alter the product experience yourself)

• Share your knowledge of ML use cases to enable other teams to build ML-powered features using the models you’ve deployed

• Write the data pipelines that feed your ML systems

What You’ll Bring

• Have 0 to 1 experience with a bias towards shipping and learning while balancing a high quality bar

• Strong product intuition — the ability to think broadly and cross-functionally about innovative ML product experiences

• Experience in NLP and information retrieval space

• Experience building and deploying models in user-facing production settings

• An ability to scope and timebox research problems and execute the findings via concrete product plans

• Breadth of experience covering classical statistical ML models, deep neural networks, and (optionally) LLMs (not building, just using) and an understanding of when its appropriate to use each

• Python expertise

• 4+ years of experience

Nice to Haves

• Previous experience with applications of instruction tuning, reinforcement learning from human feedback (RLHF), and fine-tuning (e.g. LoRA) to improve LLMs for different use cases.

• An infrastructure or platform background to set the foundation for future AI/ML hires to build off of

• Diversity of perspectives and interests. We hope to build a team that is curious, and open-minded.

• Experience working with systems & data at scale. May be building large-scale high-performance data pipelines, event ingestion systems, or generally working with larger production systems

• Experience with our current tech stack:

  • React, Typescript, Python

  • AWS services: Aurora (Postgres), Elasticache (Redis), Elastic Container Registry (ECR), ECS (Fargate), Lambda, OpenSearch

  • IaC: Terraform

  • Deployment tools: CircleCI, Netlify, Playwright

  • Observability tools: Cloudwatch, Datadog, Mezmo

Life @ Clay 

Based out of a central office on 19th Street in Manhattan’s Flatiron District. We love the energy of in-person collaboration while also offering the flexibility to work from home when needed.

• Competitive salary and role trajectory: Roles, responsibilities, and comp grow as we do

• Health insurance: Fully funded, high quality health, dental & vision coverage (including 80-100% therapy coverage)

• Visa sponsorship: We get it - it’s an arduous process, but we’re not scared of it

• Paid time off: We expect team members to take at least 3 weeks fully-disconnected per year, with a flexible vacation policy beyond that

• Free lunch: Lunch is provided in office every day

• Parental leave & fertility support: IVF fertility benefits, egg freezing, and 4 months of paid parental leave

Learn more about Clay and what it’s like to work with us right here!