Senior Technology Lead - Machine Learning/Artificial Intelligence (7-12 yrs)

Role Overview :

We are seeking a highly experienced and visionary Senior AI/ML/Generative AI Technology Lead with 7 to 12 years of hands-on experience to spearhead the architecture, development, and deployment of our next-generation AI and Machine Learning solutions.

This pivotal role demands a profound blend of technical mastery across diverse AI domains, with a particular emphasis on Generative AI and intelligent agent systems, coupled with proven expertise in MLOps, cloud infrastructure, and leading complex projects to production.

The ideal candidate will be a hands-on leader, a strategic thinker, and a mentor, capable of influencing technical direction, fostering innovation, and driving the successful delivery of high-impact AI products that solve critical business challenges.

Key Responsibilities :

- Drive the end-to-end lifecycle of machine learning models and sophisticated AI algorithms, from conceptualization and design to robust deployment and continuous optimization, addressing critical business challenges.

- Lead the development and optimization of advanced deep learning models and algorithms, focusing on enhancing performance, accuracy, interpretability, and scalability for real-world applications.

- Architect and implement highly efficient algorithms for large-scale data processing and real-time analytics, ensuring high throughput and low latency.

- Pioneer Design and Development of Intelligent Agents : Lead the strategic design, development, and implementation of cutting-edge AI agents capable of autonomous, goal-driven behavior, leveraging and innovating upon frameworks such as ReAct, AutoGPT, LangChain, and other multi-agent orchestration tools.

- Advanced Task Orchestration and Multi-Agent Collaboration : Architect sophisticated systems that enable complex task decomposition, seamless coordination of subtasks across multiple agents, and intelligent interaction with other agents or external systems to achieve highly complex objectives.

- Expert Prompt Engineering and Context Management : Define and implement advanced prompt engineering methodologies and sophisticated context management strategies to precisely guide agent reasoning, optimize dynamic memory usage, and orchestrate complex tool invocation effectively.

- Human-Agent Interaction & Robust Oversight : Design and oversee the development of intuitive and robust interfaces for effective human collaboration with AI agents, embedding critical elements like continuous feedback loops, explainability (XAI), transparent control mechanisms, and robust monitoring.

- Secure Tool and API Integration : Architect and enforce secure access and seamless integration of AI agents with external tools, APIs, and diverse data sources, enabling them to execute real-world tasks with reliability and integrity.

- Proactive Governance, Safety, and Monitoring : Establish and enforce comprehensive behavioral constraints, develop sophisticated monitoring systems for real-time detection of agent output misalignment or risks, and ensure unwavering compliance with the highest ethical and regulatory standards (e.g., responsible AI principles).

Deep Learning Expertise :

- Lead the design, implementation, and optimization of state-of-the-art deep learning models for a wide array of applications, including advanced classification, regression, and complex generative tasks (e.g., image, text, video generation).

- Drive the strategic utilization of leading frameworks such as TensorFlow and PyTorch to develop highly performant neural networks and cutting-edge deep learning architectures.

Specialized Analytics Leadership (Image, Video, Voice, Text) :

Image Analytics :

- Architect, develop, and deploy advanced image recognition and analysis models to extract deep insights from visual data.

- Expertly apply and innovate with Convolutional Neural Networks (CNNs), Vision Transformers (ViT), and other cutting-edge image processing techniques for complex problems like object detection, instance segmentation, and fine-grained classification.

Video Analytics :

- Lead the implementation of comprehensive video analysis solutions to process and interpret video data for critical tasks such as multi-object tracking, complex action recognition, anomaly detection, and event prediction.

- Leverage advanced deep learning techniques for real-time, high-volume video processing and analysis.

Voice Analytics :

- Drive the development and deployment of sophisticated models for voice recognition, advanced sentiment analysis, emotion detection, and highly accurate speaker identification.

- Apply cutting-edge Natural Language Processing (NLP) and audio signal processing techniques to extract nuanced insights from voice data.

Text Analytics :

- Champion the implementation of advanced text mining and NLP techniques to extract profound and actionable insights from vast unstructured text data.

- Lead the development of models for advanced sentiment analysis, sophisticated topic modeling, entity recognition, and text classification using state-of-the-art NLP frameworks (e.g., Hugging Face Transformers, SpaCy).

Cloud & Infrastructure Leadership :

- Define and drive the strategy for utilizing leading cloud platforms such as AWS and Azure for robust deployment, scalable management, and efficient operationalization of AI/ML models and complex infrastructure.

- Serve as the subject matter expert in leveraging advanced cloud-based tools and services, including Amazon SageMaker, Azure Machine Learning, Azure Databricks, and others, for accelerating end-to-end model development, training, and deployment.

Seamless Integration & Production Deployment (MLOps) :

- Lead the integration of AI/ML models into existing enterprise systems and complex workflows, ensuring seamless operation, minimal disruption, and maximum business impact.

- Define and implement best practices for MLOps, developing scalable APIs and robust interfaces for efficient model interaction and seamless integration with various applications.

Advanced Performance Monitoring & Optimization :

- Establish and lead comprehensive strategies for monitoring, evaluating, and troubleshooting the performance of AI/ML models and systems in production, ensuring they consistently meet and exceed predefined business objectives and KPIs.

- Drive continuous refinement, re-training, and optimization of models based on rigorous performance data analysis, A/B testing, and feedback loops.

Cross-Functional Collaboration & Mentorship :

- Collaborate extensively with data scientists, data engineers, product managers, business analysts, and other senior stakeholders to deeply understand strategic requirements and architect innovative, impactful technical solutions.

- Act as a technical leader and mentor to junior and mid-level team members, fostering a culture of technical excellence, continuous learning, and best practices within the AI/ML team.

Strategic Documentation & Reporting :

- Oversee and ensure the maintenance of comprehensive, high-quality documentation for all AI/ML models, algorithms, architecture designs, and robust deployment processes.

- Communicate complex technical findings, strategic recommendations, and project progress to both technical and executive stakeholders clearly, concisely, and effectively.

Innovation, Research & Best Practices :

- Proactively research, evaluate, and integrate the latest advancements in AI/ML/Generative AI technologies, methodologies, and academic research into our solutions.

- Lead initiatives to explore and implement new tools, frameworks, and methods to continuously enhance our AI/ML capabilities, drive competitive advantage, and foster a culture of cutting-edge innovation.

Key Requirements :

Extensive AI/ML/Generative AI Expertise :

- 7 to 12 years of progressive, hands-on experience in the design, development, and deployment of complex AI/ML solutions, with a significant and proven track record in deep learning and Generative AI.

- Demonstrable expertise in a wide range of AI domains including natural language processing, computer vision, audio processing, and statistical modeling.

- Mandatory : Proven, hands-on experience leading and executing the deployment of complex ML models into high-scale production environments with robust MLOps practices.

- Deep theoretical and practical understanding of supervised, semi-supervised, unsupervised, and reinforcement learning paradigms.

- Critical : Extensive experience with Large Language Models (LLMs), their fine-tuning, adaptation, and leading the implementation of Generative AI applications for real-world problems.

Deep Tech Stack Proficiency :

- Languages : Expert-level proficiency in Python (mandatory for advanced AI development). Experience with R and Java is a plus.

- Libraries : Mastery of TensorFlow and PyTorch, with proven experience in building and optimizing complex neural networks.

- Strong command of Scikit-learn and other relevant ML libraries.

- Generative AI Frameworks : Proven, hands-on experience with cutting-edge frameworks such as LangChain, AutoGen, CrewAI, and designing/implementing robust RAG (Retrieval Augmented Generation) pipelines and other Gen AI architectures.

- Deployment & MLOps Tools : Expert-level experience with FastAPI, Docker, and Kubernetes for building, containerizing, and orchestrating scalable AI services.

- Cloud Platforms : Extensive hands-on experience leveraging key services on both AWS (e.g., SageMaker, Lambda, Glue, Redshift, S3, EC2, ECS, EKS) and Azure (e.g., Azure Machine Learning, Azure Databricks, Azure Synapse Analytics, Azure Cognitive Services) for comprehensive AI/ML workloads.

Advanced AI Skills :

- Exceptional expertise in prompt engineering, advanced semantic understanding, and complex tool/API integration for intelligent agents.

- Deep knowledge and practical experience with advanced agent architecture design, ReAct planning, and sophisticated memory systems (e.g., Pinecone, FAISS, custom vector databases).

- Proven ability to implement and enforce guardrails, telemetry, and ensure adherence to ethical AI standards and responsible AI principles.

Data & Visualization :

- Proficiency in data visualization tools like Power BI and Tableau for communicating insights.

- Strong familiarity with big data technologies (e.g., Spark, Hadoop, Kafka) and various data storage solutions.

Education :

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a closely related quantitative field.

- A Ph.D. is a significant advantage.

Experience :

- 7 to 12 years of overall experience in software development and data science, with a significant portion dedicated to leading AI/ML initiatives and deploying production-grade models.

- Proven experience in a senior technical lead, architect, or principal engineer role within the AI/ML domain.

Compensation :

- Highly competitive salary package commensurate with experience and industry standards for a Senior AI/ML/Generative AI Technology Lead in Mumbai.

- This role offers significant growth potential and an opportunity to be a key player in our AI journey.

Location : Mumbai, India

Why Join Us?

- Impactful Innovation : Be a driving force behind transformative AI projects that directly influence [mention specific business impact or industry change, e.g., "customer engagement," "operational efficiency," "product innovation"].

- Cutting-Edge Technology : Work at the forefront of Generative AI and Agentic AI research and development, solving never-before-seen challenges in a dynamic and fast-evolving landscape.

- Leadership & Growth : Opportunity to define technical roadmaps, architect foundational AI systems, mentor high-performing teams, and grow into broader leadership and principal roles within the organization.

- Collaborative Environment : Join a vibrant, intellectually stimulating, and highly collaborative environment that values continuous learning, bold experimentation, and sharing knowledge.

- Competitive Rewards : Receive a highly competitive compensation package, comprehensive benefits, and ample opportunities for professional development and career advancement