Job
Description
Primary Responsibilities: Model Deployment: Design, code, and implement software solutions that deploy GENAI models like RAG, Agentic workflows, AI agents into production environments, ensuring scalability and reliability Data Analysis: Investigate and analyze large-scale computing frameworks and data analysis systems to derive actionable insights Stakeholder Communication: Clearly present complex analytics results and concepts to leadership and internal stakeholders, facilitating informed decision-making Cloud Development: Develop and deploy robust data pipelines and machine learning models on cloud platforms such as Azure, AWS, GCP, and Databricks, ensuring optimal performance and security AI/ML Techniques: Employ advanced AI and ML techniques, including natural language processing (NLP), natural language understanding (NLU), semantic understanding, intent classification, computer vision, deep learning, and automatic speech recognition (ASR) Deep Learning Applications: Apply deep learning technologies to enable systems to visualize, learn, and respond to complex scenarios effectively. Interactive Experiences: Adapt machine learning methodologies for applications in artificial intelligence, robotics, and other interactive user experiences Model Observability: Utilize model observability tools to gain insights into the behavior, performance, and health of deployed ML models, including tracking, alerting, and compliance monitoring MLOps Skills: Implement best practices in machine learning operations (MLOps) to streamline workflows and enhance collaboration Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Qualifications - External Required Qualifications: Bachelor of Engineering or equivalent degree 9+ years of total experience in AI/ML roles and data science Experience in establishing AI/ML best practices, standards, and ethics Basic knowledge of statistics and its application in data analysis Solid understanding of the mathematics behind machine learning (ML) and deep learning (DL) algorithms Proficiency in coding with Python, along with libraries such as pandas Proven solid grasp of machine learning and deep learning concepts and methodologies Preferred Qualifications: 2+ years of experience in developing and deploying GENAI models and agents, with familiarity in both cloud-native and cloud-agnostic environments Experience working within a healthcare or regulated industry, with a deep understanding of the unique challenges and compliance requirements Experience in mentoring and coaching AI/ML talent Experience working with cross-functional and distributed teams in a global and diverse environment Demonstrated leadership , people management , business and stake holder management and innovative problem solving skills Proven ability to work independently, manage multiple projects simultaneously, and adapt to changing priorities in a fast-paced environment Proven ability to track record of delivering high-impact AI/ML solutions for real-world problems and use cases
