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Tier-1 brand, mid-level ML role in metro with broad hiring demand increases competition.
Core ML engineering skills are transferable, though scientific and R&D experience is preferred.
Requires MSc/PhD, 5+ years, production ML, MLOps, and strong software engineering, so strict technical filters.
Design, build, and maintain scalable, production-grade machine learning systems and pipelines with modern engineering practices including CI/CD, testing, and monitoring.
Develop novel machine learning algorithms and models transitioning from research to reliable, deployable, and scalable products, including NLP, optimization, simulation, and generative AI.
Collaborate with cross-disciplinary teams to translate complex scientific and business challenges into impactful ML solutions, mentor juniors, and improve engineering standards.
MSc or PhD in quantitative fields such as Computer Science, Mathematics, Physics, or Engineering.
5+ years of hands-on experience in designing, prototyping, productionizing, maintaining, and scaling ML/data science products in complex environments.
Strong expertise in machine learning algorithms, statistical modelling, optimization, and advanced programming skills in languages like Python, Go, Java, or C++.
Experience with ML engineering practices including MLOps, model lifecycle management, CI/CD pipelines, and monitoring.
Experienced in applying ML science to build production-grade systems beyond experimental prototypes with demonstrated operational ownership.
Able to work cross-functionally with data scientists, engineers, and domain experts to translate complex problems into deployed ML products with measurable value.
Skilled in modern ML engineering, stakeholder management, and continuous improvement within high-maturity, technology-driven environments.