Machine Learning / AI Engineer

SPOTIO is a dynamic, fast-growing American start-up with a 10-year tradition of creating the #1 Sales Engagement Platform. SPOTIO's platform helps field sales teams manage sales activities, increase the productivity of sales representatives and record field sales insights. The company has offices in Dallas, Texas and Gdansk, with a development, product and QA team of 21 people in Gdansk and 50 people globally.

• At least 5 years of professional experience in ML engineering, applied data science, or a closely related role.
• Strong Python skills, with experience building and deploying production ML services (FastAPI or equivalent).
• Hands-on experience training, evaluating, and deploying gradient boosting models (LightGBM, XGBoost, or similar) in production.
• Experience with model explainability tools, particularly SHAP.
• Infrastructure-as-code experience, ideally with Terraform.
• Working knowledge of MLOps practices: model registries, versioned artifacts, drift monitoring, and automated retraining pipelines.
• Proficiency in SQL with understanding of query patterns, connection pooling, and performance considerations in high-volume environments.
• Experience with PyTorch, scikit-learn, NumPy, and Pandas (or Polars).
• Precision, proactivity, and comfort taking full ownership of systems.
• Proficiency in English.
• Education related to computer science, mathematics, statistics, or a related field.

Nice to have:

• Experience with multi-armed bandits or reinforcement learning approaches.
• Familiarity with Elasticsearch.
• Azure Event Hubs, Stream Analytics, or ADLS Gen2.
• Production experience with a major cloud platform (Azure, AWS, or GCP).
• Experience with Kubernetes in a production environment.
• Azure DevOps Pipelines or Argo CD.
• Exposure to sales CRM data, territory management, or field sales workflows.

• Own the full ML lifecycle for SPOTIO's AI features: problem framing, feature engineering, model training and evaluation, production deployment, and ongoing retraining as new data accumulates.
• Operate and evolve the production scoring service, a containerized REST API that serves real-time predictions across multiple ML capabilities for all active SPOTIO customers.
• Monitor model health across all companies and capabilities: track retrospective accuracy metrics, feature drift statistics, nightly batch success rates, and API latency through SPOTIO's observability stack.
• Manage the model retraining cycle, including assembling training datasets, evaluating candidate models against quality gates, and promoting new versions through the model registry.
• Triage and resolve production scoring failures, including upstream data access issues, feature extraction errors, and batch pipeline anomalies.
• Manage ML feedback loops, including reinforcement-style approaches such as Thompson Sampling bandits, to incorporate user behavior signals into model training over time.
• Collaborate with SPOTIO engineering to integrate ML outputs into the LLM-powered AI layer, shaping the AI-generated descriptions and next-best-action recommendations that sales reps see in the product.
• Work with product and engineering on the design and activation of new AI features beyond the current scoring suite.
• Contribute to SDLC ceremonies: architecture design, code review, CI/CD, and agile planning.

This role carries on-call responsibility for ML-related incidents. On-call rotation is shared and supported by the broader engineering team.