Product ML Engineer

Job summary

Responsibilities

We're looking for a Product ML Engineer to join one of our product experience teams — SMB, Scaler or Enterprise — and own the ML side of short, high-impact projects.

• Embed directly within a product team. Work closely with the SMB, Scaler or Enterprise team on focused ML problems tied to clear customer and business outcomes.
• Own ML projects end to end. Frame the problem, choose the approach, execute the plan, ship the feature and monitor its performance in production.
• Make the build vs. buy decision. Determine when to fine-tune or build a model yourself versus integrating an external model, API or existing library.
• Move from idea to production quickly. Work on projects scoped in weeks rather than quarters, prioritising rapid iteration and customer impact.
• Work closely with the ML team. Leverage shared infrastructure, evaluation tooling and expertise while remaining embedded in the product team's priorities and cadence.

What they're looking for

• You've shipped ML into production. You have 2+ years of hands-on experience building and shipping ML-powered products, with strong experience in PyTorch or equivalent frameworks…
• You have applied-science depth. You can fine-tune vision or diffusion models, design meaningful evaluations and debug training runs when necessary.
• You're a pragmatic builder. You care about solving the customer's problem rather than proving that your own model is the best approach.
• You're product-minded. You measure success through shipped features, user behaviour and business outcomes rather than papers or benchmarks alone.
• You're comfortable in production codebases. You can move between experimentation and production engineering, writing maintainable code that lives inside a real product.

Tech stack

• PyTorch
• TensorFlow
• JAX