Senior ML Engineer

Role Description

AI is the product. The Context Engine and Invoca's agentic AI workflows only create customer value if the models behind them are fast, reliable, and continuously improving in production. This is a hands-on role focused on production leverage, not model experimentation in isolation. You will own the layer that turns trained models into dependable, high-throughput services that Data Scientists, Applied AI Engineers, and product teams build on every day.

As a platform team, our real customers are the product teams who build on what we ship. Success in this role is measured by their outcomes:

• How quickly product teams can ship intelligent, differentiated customer experiences on top of the models and infrastructure you own.
• How reliably those experiences hold up as usage scales.
• How much your work accelerates Invoca's ability to innovate with AI.

What You'll Do

• Own Production ML as a System, Not a One-Off Deployment
  • Architect, implement, and maintain CI/CD pipelines for ML artifacts, including automated evaluation, versioning, and deployment.
  • Serve as the primary SME for operational excellence across the Invoca ML stack: uptime, latency, throughput, and cost.
  • Treat model serving as a product with real customers, the product teams who build on it, and hold yourself accountable to their ability to ship.
• Push the Limits of SLM/LLM Deployment
  • Own inference infrastructure end to end: model serving on Triton Inference Server, Baseten, and Kubernetes-based GPU infrastructure.
  • Profile and tune for low latency and high throughput; build robust, scalable APIs for internal and external model access.
  • Continuously look for step-function improvements in inference cost and speed, not just incremental tuning, so product teams never have to wait on the platform.
• Fine-Tune Models for Measurable Product Impact
  • Apply parameter-efficient fine-tuning methods (LoRA, QLoRA, PEFT) to adapt transformer-based SLMs and LLMs for high-impact NLP applications in conversation intelligence.
  • Connect fine-tuning decisions directly to the customer experiences they enable, not just benchmark scores.
• Strengthen the ML Infrastructure Everything Else Depends On
  • Contribute to model training infrastructure, data pipelines, and data lake foundations that keep the systems powering our models reliable and scalable.
  • Build evaluation and monitoring practices (Braintrust, MLflow, or equivalent) that catch regressions before customers do.
• Operate at the Intersection of ML, Product, and Engineering
  • Partner closely with Data Scientists, Data Engineers, and Applied AI Engineers to build the foundational ML systems behind Invoca's agentic AI products.
  • Work directly with product teams to understand what they need to ship, and remove whatever is standing between them and shipping it.

Qualifications

• 5+ years of ML Engineering experience with a strong production focus
• Advanced Python and deep learning proficiency (PyTorch, HuggingFace Transformers, spaCy)
• Demonstrated track record deploying and maintaining transformer-based NLP models in production
• Hands-on experience fine-tuning SLMs/LLMs (LoRA, QLoRA, PEFT) and optimizing models via quantization, batching, and throughput tuning
• Proficiency with inference infrastructure: Triton, Baseten, vLLM, TGI, SageMaker, Vertex AI, or similar
• Experience building production-grade APIs that expose ML models to downstream consumers
• Familiarity with MLOps tooling, model monitoring, and eval platforms (Braintrust, MLflow, or equivalent)
• Experience operating models in an agentic or multi-step AI workflow context is a strong plus
• B.S. in Computer Science, Engineering, Statistics, or equivalent; advanced degree a plus
• Familiarity with RLHF or preference training is a bonus

Requirements

• Success in this role will look like:
  • Product teams can ship new AI-powered features and fine-tuned models significantly faster because the serving and deployment layer you own removes friction instead of adding it.
  • AI-powered customer experiences built on your infrastructure operate reliably at scale, with latency, uptime, and cost that hold up as usage grows.
  • Product teams adopt your platform's model-serving and fine-tuning capabilities with confidence, without needing to build their own ML infrastructure expertise.
  • Your work is a visible accelerant for how quickly Invoca turns new AI capabilities into shipped, differentiated customer experiences.
  • You're recognized as the person who makes “ship an AI feature” fast and safe, not someone teams route around.

Benefits

• Flexible Time Off – We encourage a healthy work-life balance. Our flexible paid time off policy allows you to recharge and take time away as needed.
• Paid Holidays – Invoca provides 16 U.S. paid holidays, including a winter break, giving you ample opportunity to refresh and spend time with friends and family.
• Health Benefits – Our healthcare program includes medical, dental, and vision coverage, with multiple plan options so you can choose what works best for you and your family. Fertility assistance is also included.
• Retirement – Invoca offers a 401(k) plan through Fidelity with a company match of up to 4%.
• Stock Options – All employees are invited to share in Invoca’s success through stock options.
• Mental Health Program – Well-being support on a broad range of issues is available through our SpringHealth program.
• Paid Family Leave – Up to 6 weeks of 100% paid leave is provided for baby bonding, adoption, and caring for family members.
• Paid Medical Leave – Up to 12 weeks of 100% paid leave is provided for childbirth and medical needs.
• InVacation – As a thank-you to our long-term team members, we offer a bonus after 7 years of service.
• Wellness Subsidy – We provide a subsidy that can be applied toward gym memberships, fitness classes, and more.