You’ll join a modular, data-intensive platform that optimizes large-scale operations (e.g., energy/transport scheduling) via mathematical optimization. The system streams high-quality telemetry, schedules, costs, and alerts - creating ground for ML that enhances forecasting, risk assessment, and decision support. No ML is in production yet; you’ll help design and ship the first wave.ResponsibilitiesTranslate business/optimization needs into ML problemsDesign and own end-to-end data/feature pipelinesBuild, validate, and productionize models for forecasting, classification, and anomaly detection on operational dataDefine evaluation metrics and experimentation loops (offline simulation, A/B tests, post-deployment monitoring)Integrate models into microservices and optimization workflows (batch/real-time inference, APIs, containers)Establish MLOps foundations: versioning, CI/CD, monitoring, and drift detection.Collaborate closely with domain/optimization engineers and stakeholders to ensure models drive measurable impactPersonal Profile OverviewComfortable owning the full ML lifecycle (problem framing, data, model, deploy, observe)Degree in Data Science, Computer Science, Software Engineering or related fieldStability in previous employment history with a tendency to remain with employers for extended periodsExperience in managing diverse project activities (not just coding, but also requirements analysis, preparing estimations)Clear and effective communication skills, both verbal and written, and ability to convey ideas, information, and messages accurately and efficientlyProficiency in fostering effective collaboration and teamwork activitiesAbility to analyze information, assess situations, and make decisions based on sound reasoning and logical evaluationFocus on delivering exceptional customer experiences and prioritizing customer satisfactionAnalytical thinking, problem-solving abilities, and strategic approach to technical challengesTransparency in sharing information within a team and companyWillingness to acquire new knowledge and insights to enhance professional growth and performanceRequired skills3+ years of hands-on experience in applied machine learning, particularly with structured and time-series dataExperience developing models for forecasting, classification, or anomaly detection in real-world production systemsStrong experience with time-series modeling and feature engineering, including resampling, time-aligned joins, and handling irregular or sparse dataProficiency in error analysis and debugging ML models, including use of metrics like MAE, RMSE, F1, ROC-AUC, and calibration curvesUnderstanding of model explainability tools and techniques (e.g., SHAP, permutation importance, feature contribution tracking)Experience with ML versioning and reproducibility tools (e.g., MLflow, DVC, Weights & Biases)Familiarity with cloud-based ML infrastructure (AWS/GCP/Azure).English Upper-Intermediate (B2)As a plusExperience with energy/EV charging domainExperience with reinforcement learning in optimization settingsWe offerFuel your professional growth with paid online courses, conferences, certifications, English classes, a corporate library, and leadership programThrive in a culture of trust and cooperation with no time trackers and minimal bureaucracyEnjoy 20 business days of paid vacation, plus state holidays to prioritize your well-beingExperience an open-door culture, transparent communication, and top management at a handshake distanceEnjoy comfortable office vibes with no open space policy, relaxing sports areas, a spacious bar/kitchen, and moreAchieve balance with our hybrid/fully remote work modelReceive fair and competitive compensationFuel your productivity and foster a sense of community with complimentary daily lunchesParticipate in meaningful initiatives supporting Ukraine’s victoryTake flexible sick leave without burdensome documentation and access parental benefitsChoose from comprehensive medical insurance or a sports compensation packageHave fun with regular team-building activities, corporate events and celebrations, and unique initiatives like Week in Lviv