Sr. Manager, AI / ML Engineering

Description

Seeking a passionate, hands-on technical AI /ML engineering leader to join our growing team and solve exciting engineering problems in the semiconductor space. The role provides the opportunity to solve a wide range of challenges. This position will work closely with multidisciplinary teams that include product managers, data engineers, data scientists, and business stakeholders to bring AI solutions to production.

Key Responsibilities

• Design and develop ML models for high impact engineering solutions. Build, train, and optimize machine learning and deep learning models to solve complex problems using natural language processing, computer vision, and predictive analytics. Knowledge of python, Pytorch, agentic frameworks, Langchain, RAG, capability to understand and build deep learning models on cloud or on premises compute.
• Lead and mentor a team of AI/ML engineers and ML operations specialists, fostering a collaborative and innovative environment.
• Design, implement, and maintain scalable and reliable machine learning infrastructure and pipelines.
• Establish best practices for model development, deployment, monitoring, and lifecycle management.
• Collaborate with data scientists, product managers, and software engineers to deliver AI solutions aligned with business objectives.
• Manage and optimize cloud and on-premises resources for efficient training, serving, and experimentation of machine learning models.
• Ensure compliance with data privacy, security, and ethical standards in all AI/ML operations.
• Automate processes for continuous integration and deployment (CI/CD) of machine learning models.
• Drive adoption of MLOps tools and technologies, championing innovation and efficiency.
• Develop documentation, training programs, and onboarding resources for new team members and stakeholders.
• Establish metrics and KPIs to measure the quality and impact of AI/ML models in production environments.
• Stay current with industry trends, research, and emerging technologies, integrating relevant advances into operational practices.

Qualifications

• Education: Bachelor with 12+ years of professional experience in machine learning, artificial intelligence, or related fields. Preferably with a Master’s degree or A PhD or relevant research experience in Computer Science, Engineering, Mathematics, Statistics, or a related field.
• Experience managing and guiding AI/ML engineering and operations teams.
• Hands-on experience with neural networks, deep learning architectures such as CNNs, RNNs, Transformers and Generative AI.
• Exposure to MLOps practices: monitoring, scaling, and automating ML workflows
• Experience with big data platforms: Databricks, Hadoop, Spark, Dataflow, etc or comparable products
• Familiarity with advanced topics such as reinforcement learning, generative models, or explainable AI

Technical Skills

• Proficiency in programming languages such as Python (preferred), Java, Csharp, or C++ 7 years experience
• Deep understanding of machine learning frameworks: PyTorch, scikit-learn, Keras, etc.
• Experience with data manipulation tools: NumPy, SQL, Pandas
• Solid grasp of statistics, probability theory, and linear algebra
• Familiarity with cloud and Data computing platforms: Azure, Azure DevOps, DataBricks or comparable platforms like GCP, BIgQuery
• Knowledge of containerization and orchestration: Docker, Kubernetes
• Experience in deploying machine learning models to production
• Understanding of software engineering best practices: version control (Git), unit testing, CI/CD pipelines

Desired Experience and Skills

Preference for a Ph.D. in Computer Science, Engineering, Mathematics, Statistics, or a related field with 10+ years of experience in AI solutioning and delivery. Cloud and on-prem experience for solution development and MLops deployment. Multiple years of experience in taking GenerativeAI solutions to production.