AI / ML Lead

As a AI/ML Lead at Tata Technologies, you will play a pivotal role in driving the development and implementation of artificial intelligence and machine learning solutions across various industries. Our company is a leading provider of IT services and consulting, and we are committed to harnessing the power of AI and ML to transform businesses.

In this mid-senior level role, you will lead a team of data scientists and engineers to design, develop, and deploy AI/ML models that solve complex business problems. You will work closely with cross-functional teams to identify opportunities for AI/ML adoption, develop proof-of-concepts, and implement scalable solutions. Your expertise in deep learning, natural language processing, and computer vision will enable us to drive innovation and stay ahead of the competition.

The ideal candidate will have a strong background in computer science, mathematics, and statistics, with a focus on AI/ML. You should have experience in developing and deploying AI/ML models using popular frameworks such as TensorFlow, PyTorch, and Scikit-learn. Your experience in working with large datasets, data preprocessing, and feature engineering will be essential in this role.

As an AI/ML Lead, you will be responsible for:

• Leading the development of AI/ML solutions across various industries, including automotive, aerospace, and industrial equipment
• Collaborating with business stakeholders to identify opportunities for AI/ML adoption and develop business cases
• Designing and developing AI/ML models using deep learning, natural language processing, and computer vision techniques
• Working with data engineers to develop data pipelines and architectures that support AI/ML solutions
• Leading a team of data scientists and engineers to develop and deploy AI/ML solutions
• Developing and maintaining technical roadmaps and strategies for AI/ML adoption
• Collaborating with cross-functional teams to ensure AI/ML solutions are integrated with existing IT systems and infrastructure

Our company, Tata Technologies, is headquartered in Pune, India, and has a global presence with offices in North America, Europe, and Asia. We offer a dynamic work environment that encourages innovation, collaboration, and continuous learning. Our team of AI/ML experts works closely with clients to develop customized solutions that meet their specific needs.

The AI/ML Lead role at Tata Technologies requires:

• Master's degree in Computer Science, Mathematics, Statistics, or related fields
• 5+ years of experience in AI/ML, with a focus on deep learning, natural language processing, and computer vision
• Strong programming skills in Python, R, or Julia
• Experience with AI/ML frameworks such as TensorFlow, PyTorch, and Scikit-learn
• Strong understanding of computer science, mathematics, and statistics
• Experience working with large datasets, data preprocessing, and feature engineering
• Strong communication and leadership skills

If you are a motivated and experienced AI/ML professional looking to lead a team of data scientists and engineers, this role is an exciting opportunity to join a dynamic team and contribute to the development of innovative AI/ML solutions.

Qualifications for AI/ML Lead at Tata Technologies

Education:

• Master's or Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or related fields from a reputable institution.
• Relevant certifications in AI, ML, or data science are a plus.

Technical Skills:

• Proficiency in programming languages such as Python, R, or Julia.
• Experience with popular AI/ML libraries and frameworks, including TensorFlow, PyTorch, Keras, or scikit-learn.
• Strong understanding of data structures, algorithms, and software design patterns.
• Familiarity with big data technologies like Hadoop, Spark, or NoSQL databases.

Experience:

• Minimum 5-7 years of experience in AI/ML, with a focus on developing and deploying machine learning models.
• Proven track record of leading AI/ML projects, from conception to deployment, and delivering business value.
• Experience working with cross-functional teams, including data engineering, product management, and software development.

AI/ML Expertise:

• Strong foundation in machine learning fundamentals, including supervised and unsupervised learning, regression, classification, clustering, and neural networks.
• Experience with deep learning techniques, such as CNNs, RNNs, and LSTMs.
• Knowledge of natural language processing (NLP) and computer vision.
• Familiarity with reinforcement learning and transfer learning.

Leadership and Management:

• Experience in leading and mentoring teams of data scientists, engineers, and analysts.
• Strong communication and interpersonal skills, with the ability to effectively collaborate with stakeholders.
• Proven ability to drive projects from concept to delivery, and to prioritize and manage multiple projects simultaneously.

Domain Expertise:

• Experience working in industries such as automotive, aerospace, or healthcare.
• Familiarity with domain-specific challenges and opportunities for AI/ML adoption.

Tools and Technologies:

• Experience with cloud-based AI/ML platforms, such as AWS SageMaker, Google Cloud AI Platform, or Azure Machine Learning.
• Familiarity with DevOps tools like Docker, Kubernetes, or Jenkins.
• Knowledge of data visualization tools like Tableau, Power BI, or D3.js.

Business Acumen:

• Strong understanding of business operations and the ability to identify opportunities for AI/ML adoption.
• Experience with business case development, ROI analysis, and project prioritization.

Soft Skills:

• Excellent problem-solving skills, with the ability to analyze complex problems and develop creative solutions.
• Strong time management and organizational skills, with the ability to prioritize tasks and meet deadlines.
• Effective communication and presentation skills, with the ability to communicate technical concepts to non-technical stakeholders.

Tata Technologies Specific Requirements:

• Familiarity with Tata Technologies' products and services, such as automotive, aerospace, or industrial heavy equipment.
• Experience working with Tata Technologies' technology stack, including data management, analytics, and AI/ML platforms.

Nice to Have:

• Experience with Agile development methodologies and ITIL frameworks.
• Familiarity with cybersecurity best practices and data governance principles.
• Knowledge of industry-specific regulations and compliance requirements.

Key Performance Indicators (KPIs):

• Delivery of high-quality AI/ML solutions that meet business requirements.
• Leadership and mentoring of junior team members.
• Collaboration with cross-functional teams to drive business outcomes.
• Identification and prioritization of new AI/ML opportunities.

By focusing on these qualifications, the ideal candidate will possess a unique blend of technical expertise, business acumen, and leadership skills, enabling them to drive AI/ML adoption and deliver business value at Tata Technologies.

• Spearhead the development and implementation of artificial intelligence (AI) and machine learning (ML) solutions across various business functions at Tata Technologies, driving business growth and innovation.
• Collaborate with cross-functional teams to identify areas where AI and ML can be leveraged to improve operational efficiency, enhance customer experience, and drive revenue growth.
• Design, develop, and deploy AI/ML models and algorithms to solve complex business problems, using techniques such as deep learning, natural language processing, and computer vision.
• Work closely with data engineers to ensure seamless data integration, processing, and analysis, enabling the development of predictive models and data-driven insights.
• Develop and maintain large-scale AI/ML systems, ensuring scalability, reliability, and performance, while also ensuring data quality, security, and integrity.
• Foster a culture of innovation and experimentation, encouraging the adoption of new AI/ML techniques and tools, and providing technical guidance and mentorship to junior team members.
• Develop and manage project plans, timelines, and budgets for AI/ML initiatives, ensuring successful project delivery and ROI realization.
• Build and maintain strong relationships with stakeholders, including business leaders, product managers, and external partners, to identify opportunities and drive AI/ML adoption.
• Stay up-to-date with industry trends, advancements, and breakthroughs in AI/ML, applying this knowledge to drive innovation and improvement in Tata Technologies' AI/ML capabilities.
• Develop and implement AI/ML-related metrics and KPIs to measure the effectiveness and impact of AI/ML solutions, and make data-driven decisions to optimize their performance.
• Ensure AI/ML solutions are developed and deployed in accordance with Tata Technologies' data governance policies, ethics, and regulatory requirements.
• Lead the development of AI/ML-related documentation, including technical documentation, user manuals, and training materials.
• Provide technical expertise and support to business stakeholders, helping them to understand and leverage AI/ML solutions to drive business outcomes.
• Develop and manage AI/ML talent pipeline, identifying skill gaps and creating plans to address them, while also fostering a culture of learning and development.
• Collaborate with external partners, vendors, and research institutions to leverage their expertise, technologies, and innovations in AI/ML, driving business value and growth.
• Ensure seamless integration of AI/ML solutions with existing IT infrastructure, applications, and systems, using APIs, microservices, and other integration techniques.
• Develop business cases and proposals for AI/ML initiatives, including cost-benefit analyses, return on investment (ROI) calculations, and risk assessments.
• Manage and mitigate risks associated with AI/ML solutions, including data quality, model bias, and security risks, ensuring the reliability and trustworthiness of AI/ML systems.
• Develop and maintain technical roadmaps for AI/ML, aligning with Tata Technologies' overall business strategy and technology vision.
• Participate in industry conferences, meetups, and events, sharing knowledge, expertise, and best practices in AI/ML, and staying up-to-date with the latest trends and advancements.
• Lead and participate in hackathons, ideathons, and innovation challenges, driving innovation and creativity in AI/ML, and identifying new opportunities and solutions.
• Build and maintain a network of AI/ML professionals, researchers, and experts, fostering collaboration, knowledge-sharing, and innovation in the field.

Tata Technologies AI/ML Lead Selection Process

Overview of the Selection Process

• The selection process for the AI/ML Lead role at Tata Technologies is designed to assess the candidate's technical expertise, leadership skills, and fit with the company culture.
• The process consists of multiple stages, each evaluating a specific aspect of the candidate's profile.

Stage 1: Initial Screening

• The initial screening is a 30-minute phone call with the recruiter to assess the candidate's background, experience, and qualifications.
• The recruiter will review the candidate's resume and ask questions to gauge their interest in the role and the company.
• The candidate will also be asked to provide a brief overview of their experience in AI/ML, including their current role, responsibilities, and achievements.

Stage 2: Technical Assessment

• The technical assessment is a 2-hour online test that evaluates the candidate's technical skills in AI/ML.
• The test consists of multiple-choice questions, coding challenges, and problem-solving exercises.
• The candidate will be assessed on their knowledge of:
  • Machine learning algorithms and techniques
  • Deep learning frameworks (e.g., TensorFlow, PyTorch)
  • Natural language processing (NLP) and computer vision
  • Data preprocessing, feature engineering, and model evaluation

Stage 3: Technical Interview

• The technical interview is a 60-minute video conference call with the hiring manager and technical team members.
• The candidate will be asked to:
  • Provide a detailed overview of their experience in AI/ML, including projects and achievements
  • Discuss their approach to solving complex technical problems
  • Explain their knowledge of AI/ML concepts, including architectures, algorithms, and tools
  • Answer technical questions and provide examples of their work

Stage 4: Leadership and Behavioral Interview

• The leadership and behavioral interview is a 60-minute video conference call with the hiring manager and HR representative.
• The candidate will be asked to:
  • Discuss their leadership style and experience in leading teams
  • Provide examples of their achievements in AI/ML, including successes and failures
  • Explain their approach to collaboration, communication, and stakeholder management
  • Answer behavioral questions, such as:
    • Tell me about a time when you had to make a difficult technical decision.
    • Can you describe a project you led and the results you achieved.

Stage 5: Case Study Presentation

• The case study presentation is a 30-minute video conference call with the hiring manager and technical team members.
• The candidate will be provided with a business problem related to AI/ML and will be asked to:
  • Analyze the problem and propose a solution
  • Present their approach, including data preprocessing, model selection, and evaluation metrics
  • Discuss the technical and business implications of their solution

Stage 6: Final Interview and Offer

• The final interview is a 30-minute video conference call with the hiring manager and HR representative.
• The candidate will be asked to:
  • Discuss their salary expectations and benefits
  • Review the terms and conditions of the offer
  • Ask questions about the company, role, and future prospects
• The candidate will receive a formal offer letter outlining the terms and conditions of employment.

Tips for Preparation

• Review the fundamentals of AI/ML, including machine learning algorithms, deep learning frameworks, and NLP.
• Practice coding challenges and problem-solving exercises on platforms like LeetCode, HackerRank, or Kaggle.
• Prepare examples of your experience in AI/ML, including projects, achievements, and successes.
• Develop a strong understanding of the company, role, and industry trends.
• Practice leadership and behavioral questions, using the STAR method to structure your responses.
• Prepare a concise and clear presentation for the case study presentation.

Company Overview

• Tata Technologies is a leading global provider of engineering services and solutions, with a strong presence in the automotive, aerospace, and industrial equipment industries.
• Headquartered in Pune, Maharashtra, India, the company has been a part of the Tata Group since 1981.
• With over 35 years of experience, Tata Technologies has established itself as a trusted partner for original equipment manufacturers (OEMs) and suppliers, delivering innovative solutions that enhance product performance, reduce costs, and accelerate time-to-market.

Work Culture

• Collaborative and dynamic work environment that encourages innovation, creativity, and growth.
• Strong emphasis on teamwork, with cross-functional teams working together to deliver projects.
• Flexible work arrangements, including remote work options, to support work-life balance.
• Access to cutting-edge technologies and tools, enabling employees to stay up-to-date with industry trends.

Employee Benefits

• Competitive salary and benefits package, including:
  • Health insurance with comprehensive coverage
  • Retirement plan with company match
  • Paid time off (vacation, sick leave, and holidays)
  • Employee assistance program (EAP) for mental health and wellness
• Opportunities for professional growth and development, including:
  • Training and development programs
  • Mentorship and coaching
  • Career progression opportunities
• Access to employee wellness programs, including:
  • Fitness centers and wellness initiatives
  • Employee recognition and reward programs

Diversity, Equity, and Inclusion

• Strong commitment to diversity, equity, and inclusion (DEI), with a focus on:
  • Creating a diverse and inclusive work environment
  • Fostering a culture of equality and respect
  • Providing opportunities for underrepresented groups
• Employee resource groups (ERGs) and diversity networks to support and connect employees from diverse backgrounds.

Sustainability and Social Responsibility

• Strong focus on sustainability and social responsibility, with initiatives aimed at:
  • Reducing environmental impact
  • Promoting sustainable practices
  • Supporting local communities
• Participation in community development programs, including:
  • Education and skills development initiatives
  • Health and wellness programs
  • Disaster relief and response efforts

Innovation and Technology

• Strong emphasis on innovation and technology, with:
  • State-of-the-art infrastructure and facilities
  • Access to cutting-edge technologies and tools
  • Opportunities for experimentation and prototyping
• Focus on digital transformation, including:
  • Development of digital products and services
  • Implementation of Industry 4.0 technologies
  • Use of data analytics and artificial intelligence

Leadership and Management

• Experienced and visionary leadership team, with:
  • Strong industry expertise
  • Proven track record of success
  • Commitment to employee growth and development
• Collaborative and transparent management style, with:
  • Regular communication and feedback
  • Opportunities for employee input and suggestions
  • Focus on employee engagement and satisfaction

Employee Development

• Strong focus on employee development, with:
  • Training and development programs
  • Mentorship and coaching
  • Career progression opportunities
• Opportunities for:
  • Professional certifications and credentials
  • Industry conferences and events
  • Networking and community engagement

Work-Life Balance

• Support for work-life balance, with:
  • Flexible work arrangements
  • Employee wellness programs
  • Paid time off and leave policies
• Encouragement for employees to prioritize self-care and well-being.

Security and Data Protection

• Strong commitment to security and data protection, with:
  • Robust data protection policies and procedures
  • Regular security audits and assessments
  • Compliance with industry standards and regulations.

Infrastructure and Facilities

• State-of-the-art infrastructure and facilities, including:
  • Modern office spaces
  • Advanced technology and equipment
  • Access to recreational facilities and amenities.