Team Lead / Senior ML Engineer - ETA & Prediction Systems

Remote/Full-time Competitive salary in USD – $6k-$8k

About Rafeeq

Rafeeq is a rapidly growing on-demand delivery platform dedicated to providing a fast, reliable, and seamless experience for our customers, partners, and riders. We are building the future of delivery, and we are looking for talented and passionate individuals to join our team and help us solve the complex challenges of a modern logistics network.

The Role

We are seeking a Team Lead / Senior ML Engineer to lead our ML team while working hands-on to build our core ETA and time prediction systems. This is a dual-impact role: you will provide technical leadership and mentorship to the team while personally owning and developing critical prediction models that power our delivery platform.

What Makes This Role Unique

• Leadership + Hands-On: You'll lead a team of 2-3 ML engineers while building production models yourself
• Core Problem: Focus on solving our #1 challenge - accurate ETA prediction for food delivery. Also, lead dispatch, surge pricing and incentives optimization, which are heavily based on ETA
• Founding Team: Shape the ML function from the ground up in a fast-growing startup
• Global Team: Work with international talent, remote-first culture, compensation in foreign currency

What You'll Do

Technical Leadership (40% of time)

• Lead and mentor a small team of senior ML engineers working on dispatch, surge pricing, and incentive systems
• Define technical roadmap and architecture for ML systems across the platform
• Establish best practices for model development, deployment, and monitoring
• Conduct final interviews for ML team candidates (working closely with HR)
• Collaborate with Product and Engineering leadership on strategic initiatives

Hands-On ML Engineering (60% of time)

• Own ETA Prediction Systems: Design, build, and deploy ML models for restaurant preparation time, courier travel time, and dynamic delivery estimates
• Solve the Food Delivery Challenge: Tackle our critical ETA accuracy problem which impacts customer satisfaction and operational efficiency
• Feature Engineering: Build robust pipelines for temporal, geographic, and contextual data
• Model Development: Research and implement state-of-the-art techniques including time-series models, deep learning (LSTMs, Transformers), and ensemble methods
• Production Deployment: Take models from research to production in real-time, low-latency environments
• A/B Testing & Iteration: Design experiments to measure model impact and continuously improve accuracy

Cross-Functional Collaboration

• Work closely with Product team to understand business requirements and priorities
• Partner with Engineering to integrate ML models into production systems
• Collaborate with Product Analyst to define metrics and measure success
• Present results and insights to stakeholders across the organization

What We're Looking For

Required Qualifications:

• 5+ years of hands-on ML/Data Science experience with at least 2+ years in a technical leadership role (team lead, tech lead, or senior IC with mentorship responsibilities)
• Proven expertise in time-series forecasting and prediction models (ARIMA, Prophet, LSTM, Transformers, or similar)
• Production ML experience: Track record of deploying models in high-throughput, low-latency environments
• Strong programming skills in Python; expert-level knowledge of ML frameworks (TensorFlow, PyTorch, Scikit-learn)
• Deep SQL proficiency for feature engineering and data analysis
• Leadership experience: Comfortable mentoring engineers, conducting interviews, and making technical decisions
• Communication skills: Ability to explain complex technical concepts to both technical and non-technical audiences
• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or related field

Strongly Preferred:

• Experience in logistics, food delivery, or ride-hailing companies (Yandex, Delivery Club, Ozon, WB, Magnit etc.)
• Domain expertise in ETA prediction, routing, or travel time estimation
• Experience with geospatial data and libraries (PostGIS, GeoPandas, H3)
• Familiarity with MLOps, model monitoring, and experimentation frameworks
• Experience with real-time streaming technologies (Kafka, Kinesis)
• Track record of mentoring and growing junior engineers

Why Join Rafeeq?

• Impact: Your models will directly affect millions of deliveries and be the foundation of our platform
• Leadership Opportunity: Build and lead the ML function in a high-growth startup
• International & Remote: Work from anywhere, collaborate with global talent, get paid in USD/EUR
• Fast Hiring: We move quickly (2-3 months typical, often faster for strong candidates)
• Competitive Compensation: Market-rate salary in foreign currency + equity
• Ownership: Shape technical direction and own critical business problems
• Growth: Opportunity to scale the team and your role as we grow

Hiring Process

1. Initial screening: HR team reviews applications
2. Team conversation: Chat with the ML team to discuss technical approach and experience
3. Final interview: Technical deep-dive covering both leadership and hands-on ML skills
4. Offer: Typically 2-3 weeks from first contact to offer

Success Metrics - First 90 Days

• Establish baseline ETA accuracy and identify top 3-5 improvement opportunities
• Ship first iteration of improved ETA model to production
• Build monitoring dashboards for model performance
• Hire or begin hiring process for 1-2 additional ML engineers
• Establish weekly team rhythm and technical roadmap for Q2-Q3