Senior Associate AI ML Engineer

MSCI Services

2 - 5 years

4 - 7 Lacs

pune

Posted:3 days ago| Platform:

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Skills Required

cvs gcp data modeling machine learning data structures data processing open source monitoring python recruitment

Work Mode

Work from Office

Job Type

Full Time

Job Description

Architect, build, and maintain scalable AI/ML and GenAI solutions for enterprise applications.

Actively contribute to AI strategy and roadmap in collaboration with leadership and product teams.

Ensure robustness, reliability, and optimization of production-grade data pipelines and ML systems.

Drive end-to-end AI/ML lifecycle from ideation to deployment and monitoring.

Your Key Responsibilities

We are looking for a seasoned AI/ML engineer with a deep passion for data and innovation, a proactive mindset, and strong ownership of solutions. You will play a pivotal role in shaping our generative AI initiatives, delivering impactful and scalable intelligence across business verticals within Sustainability and Climate Org.

Lead the design and implementation of machine learning, deep learning, and GenAI systems.
Collaborate across engineering, product, domain experts, and senior leadership to identify and solve high-impact problems with AI.
Architect clean, maintainable, and efficient ML and data pipelines using modern frameworks and cloud services.
Develop and deploy AI models into production environments, ensuring resilience, scalability, and low latency.
Stay ahead of the curve in GenAI advancements and infuse them into real-world use cases.
Champion best practices in model training, evaluation, interpretability, and governance.
Guide and mentor junior team members, fostering innovation and excellence.

Your skills and experience that will help you excel

Strong programming skills in Python, with hands-on experience in ML libraries like TensorFlow, PyTorch, HuggingFace Transformers, Scikit-learn, etc.
Proven expertise in building and deploying AI/ML systems at scale (batch or real-time).
Practical experience with GenAI techniques including LLMs, fine-tuning, RAG, embeddings, prompt engineering, etc.
Solid understanding of MLOps best practices and familiarity with tools like MLflow, Airflow, Kubeflow, and Docker/Kubernetes.
Deep knowledge of data structures, algorithms, and software engineering principles.
Strong grasp of data modeling, feature engineering, and large-scale data processing with Spark or similar technologies.
Experience with cloud platforms (AWS, Azure, GCP) and their respective AI toolkits.
Excellent communication skills and ability to translate technical concepts to non-technical stakeholders.
Comfortable working in fast-paced environments and navigating ambiguity.
Self-motivated and driven by impact, with a strong sense of ownership and initiative.

Experience with multimodal AI (text, vision, audio).
Publications, open-source contributions, or patents in AI or ML.

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