Only 24h Left) AI/ML Team Lead

Job Title: AI/ML Team Lead

Job Location: Hinjewadi Phase 1, Pune (Work from Office)

Experience: 5+ Years

Shift: 1:00 PM to 10:00 PM

Job Description:

· 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.

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