Sr Machine Learning Engineer

Job Overview:

You will prototype, design, and implement predictive models and algorithms. This role involves leading the full model lifecycle including data cleansing, feature engineering, model selection, and production deployment. You'll work cross-functionally with business and product teams to deliver impactful ML solutions, particularly in vehicle telemetry and video analysis.

Key Responsibilities:

• Prototype, design, and implement predictive models and algorithms.
• Lead the complete model lifecycle: data cleansing, feature creation, iterative model selection.
• Write maintainable, extensible, and tested code following standards.
• Produce specifications and determine operation feasibility.
• Troubleshoot, debug, and upgrade existing systems.
• Use statistical and machine learning techniques to build scalable solutions for telemetry and video data.
• Perform R&D to drive discovery of next-gen mobility products.
• Establish automated processes for large-scale data analysis, model training/validation/implementation.
• Promote adoption of best practices across teams.
• Deliver production-ready code.
• Collaborate with Product Owners to define KPIs for ML initiatives.
• Stay up to date on research methodologies and emerging technologies.
• Present findings to both technical and non-technical stakeholders.
• Work within constraints of time, budget, and resources in alignment with global vision.
• Collaborate with product, engineering, and business teams to meet customer needs.

Required Qualifications:

• 5+ years of experience in Data Science or Software Engineering roles.
• 3+ years of experience in Machine Learning, Computer Vision, Signal Processing, or NLP.
• Strong programming skills in Python (including NumPy) and SQL.
• Hands-on experience with Apache Spark in production environments.
• Solid understanding of algorithm design and complexity analysis.
• Experience building ML pipelines in production.
• Knowledge of CI/CD, containerization, and deployment practices.
• Experience working in Agile environments.