Job
Description
Senior Developer: 4.5-8yrs Manager: 8 -12yrs Mandatory Skills: DS exp with NLP and GEN AI Development (Mandatory) with AWS OR Azure exp (Mandatory), Python Location: Hyderabad & Bengaluru Mode of interview: Virtual Note: 3/5 days a week WFO Ready to relocate to Hyderabad or Bengaluru upon selection Notice Period: immediate to 60Days Job Title: Data Scientist Job Summary: We are looking for a seasoned Data Science senior roles with a minimum of 5+ years of experience in Data Science and Machine Learning to lead our AI team. The ideal candidate will have a strong background in NLP, Transformers, Generative AI, Responsible AI and MLOps, as well as experience in deploying AI solutions across various cloud platforms. This role requires a combination of technical acumen, leadership skills, and a strategic mindset to drive AI initiatives that align with our business objectives. Key Responsibilities: Leadership: Direct and support the AI team in developing and implementing advanced AI/ML solutions, ensuring projects align with the company's strategic goals. Project Management: Oversee the entire lifecycle of AI projects, from ideation to deployment, prioritizing tasks, and managing resources to meet deadlines and deliverables. Technical Mastery: Utilize expertise in Python, NLP, Transformers, and Generative AI to lead technical innovation and maintain high standards of excellence within the team. Cloud and MLOps Integration: Leverage cloud platforms such as AWS for deployment and incorporate MLOps practices to enhance model development, deployment, and monitoring. System Architecture: Architect scalable, reliable, and high-performing AI systems that integrate seamlessly with existing infrastructure. Stakeholder Collaboration: Engage with stakeholders to convert business challenges into analytical questions, fostering a data-driven culture and driving impactful solutions. Team Development: Mentor team members, promote professional growth, and cultivate a culture of innovation and continuous improvement. Ethical AI Implementation: Uphold ethical standards in AI practices, ensuring models are fair, transparent, and accountable. Effective Communication: Develop and deliver clear, concise presentations to communicate complex technical details to diverse audiences, facilitating understanding and buy-in. Requirements: Degree in Computer Science, Engineering, or a related technical field at the bachelor's or master's level; candidates with a Ph.D. will be given preference. At least 5+ years of professional experience in the realm of Data Science and Machine Learning, including a leadership role with a documented history of success. Expertise in Python programming and experience with AI/ML libraries such as TensorFlow or PyTorch. Comprehensive understanding of Natural Language Processing (NLP) and hands-on experience with Transformer architectures. Proficient in leveraging AWS cloud platforms for the deployment of AI-driven solutions. Manage AWS cloud infrastructure and services including S3, EC2, Lambda, RDS, Glue, Sagemaker, EMR, and Step Functions to build and deploy scalable machine learning models. Solid grasp of MLOps concepts and practical experience with tools such as Docker, Kubernetes, and Git for operational efficiency. Capable of architecting and executing CI/CD workflows and managing infrastructure as code using tools like Terraform or AWS CloudFormation. Exceptional problem-solving abilities, analytical mindset, and effective communication skills. Established expertise with a minimum of 8 years in a technical capacity concentrating on AI/ML applications. Deep knowledge of AI/ML frameworks, NLP techniques, and Transformer-based model implementations. Proficiency in MLOps methodologies, including familiarity with LLMOps. Experience in developing APIs using frameworks such as FastAPI. Understanding of container orchestration using AWS EKS and familiarity with infrastructure frameworks like Bedrock. Oversee ethical AI practices, ensuring fairness, accountability, and transparency in AI systems. Expert in AI governance, implementing and monitoring responsible AI frameworks. Manage risk and compliance with regulatory and ethical standards for AI deployment. Champion ethical decision-making in AI development and operational processes.
