Engineering Manager - AI / ML

Requirements:

• B. Tech in computer science or related field from a Tier-1/2 university.
• 8+ years of AI/ML Engineering experience.
• 3+ years of experience managing a small team of ML/AI engineers.
• Track record of shipping production, enterprise-scale AI applications and data science products.
• Expertise in more than one of the AI/ML domains (Computer vision/NLP/Automation/Predictive Modelling/GenAI, etc. ).
• Expert knowledge of Python/SQL and AI/ML libraries (tensorflow/PyTorch/SciKit/Seaborn, etc. )
• Deep experience with additional server-side frameworks and technologies such as FastAPI, Node.js, Flask, Django, etc.
• Knowledge of client-side technologies, experience in deploying and integrating AI services on/with Mobile/Web applications (Android, iOS, React, JavaScript)
• Experience working in accordance with Dev/Sec/Ops principles.
• Familiarity with industry deployment best practices using CI/CD tools, MLOps, LLMOps and infrastructure as code (Jenkins, Docker, Kubernetes, Git, etc. )
• Strong computer science fundamentals in data structures, algorithms, automated testing, object-oriented programming, performance complexity, and implications of computer architecture on software performance.

Behavioural/Soft Skills:

• Strong interpersonal and communication skills, including the ability to explain and discuss technicalities of solutions, algorithms and techniques with colleagues and clients from other disciplines.
• Curiosity, proactivity and critical thinking.
• Experience working according to agile principles (Working knowledge of JIRA).
• Ability to collaborate with people at all levels and with multi-office/region teams.
• Ability to work independently and juggle priorities to thrive in a fast-paced and ambiguous environment, while also collaborating as part of a team in complex situations.

Good to have:

• Experience with Cloud platforms and services (AWS, Azure, GCP, etc. )
• Experience working with Big Data using PySpark/HIVE/Hadoop.

Skills

AI, ML, PyTorch, Python, TensorFlow, machine learning, scikit-learn