Machine Learning Engineer

Role: ML Engineer

Years of Experience: 12 to 18 Years

Location: Anywhere in India

Roles and Responsibilities:

Lead the design, development, and deployment of advanced AI and data science methodologies, including NLP, Machine Learning, and Deep Learning, to deliver scalable solutions for complex business challenges.

Oversee the end-to-end lifecycle of large-scale data science and AI projects, from data acquisition and feature engineering to model development, deployment, and post-production monitoring, ensuring measurable business value.

Provide strategic direction to the data science roadmap, identifying high-impact opportunities for innovation and guiding the team toward delivering actionable, production-ready insights.

Represent the data science team in executive forums, steering committees, and client engagements, advocating for data-driven decision-making and championing enterprise-wide adoption of applied AI solutions.

Collaborate with cross-functional teams—including product, engineering, and business stakeholders—to conceptualize, prototype, and implement scalable AI models across areas such as Natural Language Processing, Predictive Analytics, Recommender Systems, and Large Language Models (LLMs).

Design robust experimentation frameworks, validate algorithms, and ensure compliance with responsible AI practices around fairness, transparency, and interpretability.

Stay abreast of emerging developments in AI/ML, data engineering, and MLOps, integrating state-of-the-art techniques into business applications and contributing thought leadership through internal knowledge sharing.

Translate complex analytical outcomes into clear, impactful narratives for both technical and non-technical stakeholders, providing evidence-based insights to inform strategic decisions.

Mentor and guide a team of data scientists and analysts, fostering a culture of technical excellence, continuous learning, and collaboration.