Job Description

ID: 917 | 5-7 yrs | India | careers

Job Title:

AI/ML Team Lead

Job Location:

Hinjewadi Phase 1, Pune

Experience:

5 Years AI/ML Development and 2 Years of managing AI/ML team

Shift:

1 PM to 10 PM

:

You will be responsible for managing a team of AI and machine learning engineers, guiding them to create cutting-edge algorithms and solutions, and collaborating with cross-functional teams to integrate AI/ML models into production systems. As an AI/ML Team Lead, you will play a pivotal role in defining the strategic direction for AI initiatives while ensuring timely delivery of high-impact projects.

Key Responsibilities:

Team Leadership and Management

Lead and manage a team of AI/ML engineers and data scientists, setting clear goals, providing mentorship, and promoting a collaborative and growth-focused culture.
Foster innovation and create an environment that encourages creative problem-solving and the application of state-of-the-art machine learning techniques.
Conduct performance reviews, provide feedback, and guide career development for team members.
Promote a collaborative team environment by facilitating team meetings, brainstorming sessions, and knowledge-sharing activities.

AI/ML Solution Design and Development

Architect and design AI/ML models for a variety of use cases, such as predictive analytics, natural language processing (NLP), computer vision, recommendation systems, and optimization problems.
Collaborate with product managers and stakeholders to understand business requirements and translate them into effective AI/ML solutions.
Oversee the entire machine learning pipeline, including data collection, preprocessing, feature engineering, model selection, evaluation, and deployment.
Develop and implement AI/ML algorithms and integrate them into production systems to solve complex business problems and enhance the overall user experience.

Model Training, Optimization, and Deployment

Monitor and maintain model performance, ensuring that the deployed models remain accurate and efficient over time.
Evaluate and improve existing AI/ML models, identifying areas for optimization and implementing solutions to enhance performance (e.g., accuracy, speed, scalability).
Lead the deployment and integration of machine learning models into production environments, working closely with DevOps and infrastructure teams.
Implement best practices for model versioning, monitoring, and continuous integration/continuous deployment (CI/CD).

Research and Innovation

Stay up-to-date with industry trends and cutting-edge research in AI/ML and related fields.
Evaluate and prototype new AI/ML technologies, tools, and frameworks that could improve the company's offerings or solve business problems more efficiently.
Publish research papers, participate in conferences, or collaborate with academia to stay at the forefront of AI research and development.

Cross-Functional Collaboration

Collaborate with cross-functional teams, such as engineering, product, and business teams, to ensure AI/ML solutions align with company objectives and technical requirements.
Act as a key stakeholder in data strategy, ensuring that AI/ML initiatives are aligned with broader company goals and available data resources.
Communicate complex AI/ML concepts to non-technical stakeholders in a clear, concise manner to support decision-making processes.

Documentation and Reporting

Document AI/ML processes, methodologies, and algorithms for internal knowledge sharing and compliance purposes.
Provide regular progress updates to senior leadership, highlighting key milestones, results, and challenges.
Create comprehensive reports that include model performance analysis, business impact, and insights gained from AI projects.

Required Qualifications:

Educational Background


Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, or a related field.

Professional Experience


5+ years of experience working in AI/ML development, with a proven track record of designing, deploying, and managing machine learning models and solutions.
2+ years of experience in a leadership or managerial role, overseeing a team of AI/ML engineers or data scientists, and driving projects to completion.
Strong experience in modeling and designing machine learning solutions across various domains (e.g., NLP, computer vision, predictive analytics, etc.).
Experience working with big data tools and frameworks (e.g., Hadoop, Spark, Kafka) and knowledge of handling large datasets for training models.

Technical Skills


Proficiency in machine learning frameworks and libraries such as TensorFlow, PyTorch, Keras, Scikit-learn, XGBoost, etc.
Deep understanding of algorithms in supervised, unsupervised, and reinforcement learning, as well as optimization techniques.
Strong knowledge of programming languages such as Python, R, Java, and SQL, with experience in writing production-ready code.
Familiarity with cloud platforms (AWS, Google Cloud, Azure) for deploying and managing ML models.
Experience with containerization (Docker, Kubernetes) for deploying models and building scalable AI infrastructure.
Experience with model deployment and scaling, using tools like MLflow, TensorFlow Serving, or other deployment frameworks.


Soft Skills


Excellent leadership and people management skills, with the ability to motivate and guide a team toward achieving common goals.
Strong problem-solving and analytical skills, with the ability to approach complex technical challenges and derive creative solutions.
Excellent communication skills, both written and verbal, with the ability to explain complex AI/ML concepts to non-technical stakeholders.
Collaborative mindset, capable of working cross-functionally with engineering, product, and business teams.

Preferred Qualifications


Familiarity with advanced deep learning techniques such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), transformers, etc.
Experience with AI/ML in production environments, understanding how to manage model lifecycle, retraining, and continuous model improvement.
Experience in agile development environments, contributing to sprint planning, standups, and retrospectives.
Experience in specific domains such as healthcare AI, financial technology, or security AI is a plus.