Hi, We're Evlo AI!

About The Role

​

The role owns the design, training, and production deployment of machine learning systems that directly power core product features - spanning tabular ML, NLP, and increasingly LLM-based workflows.

​

Working in a small, senior team of ML engineers and data scientists, this person will tackle problems where model performance, inference latency, and reliability all matter - and ship systems that run in production, not just in notebooks.

​

Key Responsibilities

​

• Design, train, and evaluate ML models (classification, ranking, NLP, and recommendation use cases) for production workloads
• Build and maintain feature pipelines in Python and SQL, ensuring consistency between training and online serving paths
• Deploy and version models using Docker, Kubernetes, and cloud ML platforms (SageMaker, Vertex AI, or Azure ML), with automated CI/CD for model releases
• Instrument models for monitoring: track drift, latency, and business metrics with alerting and automated retraining triggers
• Collaborate with data engineering to build reliable data pipelines using Spark, Airflow, and modern data stack tooling
• Introduce and champion LLM-based capabilities where they add value - RAG systems, embeddings, fine-tuning - with rigorous evaluation
• Contribute to code reviews, design docs, and the team's ML engineering standards

​

What We Are Looking For

​

• 3–7 years of experience in machine learning engineering, applied ML, or a closely related role, with multiple production model deployments
• Expert-level Python and hands-on depth in at least one major framework: PyTorch, TensorFlow, or scikit-learn
• Production experience with cloud ML platforms and MLOps tooling (MLflow, model registries, CI/CD for ML)
• Strong ML fundamentals: feature engineering, evaluation design, regularization, and handling class imbalance and drift
• Experience with containerized deployment (Docker, Kubernetes) and serving systems such as TorchServe, Triton, or FastAPI
• MS or BS in Computer Science, Statistics, Engineering, or equivalent practical experience

About The Role

​

The role owns the strategy and roadmap for a B2B SaaS product line serving data and analytics teams, bridging engineering execution and business outcomes across the full product lifecycle.

​

You will work closely with engineering leads, designers, and go-to-market teams to define what gets built, why it matters, and how success is measured — shipping features that hundreds of enterprise customers rely on daily.

​

Key Responsibilities

​

​

• Own the product roadmap for a core platform area, translating business goals into a prioritized backlog that engineering teams can execute against
• Write clear product requirements, user stories, and acceptance criteria; run backlog grooming and sprint planning with engineering in Jira and Confluence
• Analyze product usage data using SQL, Amplitude, and internal dashboards to identify friction points, validate hypotheses, and inform prioritization decisions
• Partner with design on wireframes and prototypes in Figma; run usability sessions and customer discovery calls to pressure-test ideas before build
• Define and track success metrics (activation, retention, feature adoption) and present quarterly roadmap reviews to executive leadership
• Coordinate cross-functional launches with marketing, sales, and customer success, including enablement materials and phased rollout plans
• Serve as the voice of the customer in technical tradeoff discussions, working with engineers to scope solutions that balance speed, quality, and scalability

​

What We Are Looking For

​

​

• 3–6 years of product management experience, including at least 2 years owning a B2B or technical product end-to-end
• Hands-on SQL proficiency and comfort analyzing product data independently — not relying on others to pull numbers
• Track record of shipping features with cross-functional engineering teams in an Agile environment; fluency with Jira, Confluence, and standard PM tooling
• Strong written communication: crisp PRDs, clear stakeholder updates, and executive-ready narrative documents
• Experience conducting customer discovery and translating qualitative feedback into roadmap decisions
• Bachelor's degree in a technical field, or equivalent practical experience working closely with software engineers
• Bonus: experience with developer-facing products, APIs, or data infrastructure; familiarity with pricing and packaging decisions; technical background as an engineer or analyst