Ml Engineer Jobs

About The Position

Requirements

• Knowledge of Machine learning algorithms, deep learning frameworks, Cloud AI technologies, GenAI technologies and emerging Agentic AI technologies.
• Knowledge of Cloud platforms (e.g., AWS, Azure, GCP) for scalable AI/ML development.
• Knowledge of Responsible AI principles, including bias mitigation and ethical deployment.
• Knowledge of ML Ops best practices including CI/CD for ML, model monitoring, and versioning.
• Proficient in Python and common ML/AI libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Strong understanding of data engineering, SQL, and feature engineering.
• Direct experience with cloud services such as AWS Sagemaker, Lambda, ECS, S3, and IAM.
• Familiarity with containerization (Docker) and orchestration (e.g., Airflow, Kubeflow).
• Working with version control and collaboration tools (Git, Jira, Confluence).
• Ability to build robust, scalable, and efficient AI/ML solutions in cloud-native environments.
• Ability to translate ambiguous business problems into clear, technical ML/AI tasks.
• Ability to communicate complex ideas clearly to technical and non-technical stakeholders.
• Ability to learn and adapt quickly to emerging AI technologies, techniques, and tools.
• A bachelor's degree in computer science, information technology, engineering, or a related field is required. However, equivalent related experience and/or education may be considered as a substitute for the degree requirement upon evaluation.
• 5+ years of experience designing and deploying ML/AI solutions in real-world environments.
• Or a combination of 8 or more years of experience of software development/engineering, of which three or more years are AI/ML experience.
• Proven experience with GenAI tools and technologies (e.g., LLMs, prompt engineering, Vector databases, RAG, fine-tuning)

Nice To Haves

• Master’s or PhD in a related technical field.
• Hands-on experience with agentic AI frameworks.
• Prior contributions to open-source AI/ML projects or published research.
• AI/ML certifications from cloud providers
• Experience in highly regulated industries (e.g., healthcare, finance) a plus.

Responsibilities

• Design, develop, and deploy production-grade traditional ML models (e.g., regression, classification, clustering, recommender systems) for a variety of business use cases.
• Design, build and operationalize Gen AI (such as Retrieval Augmented Generation) and emerging Agentic AI solutions to address domain specific needs, improve user experiences and automate business workflows.
• Design, maintain, and optimize end-to-end AI/ML pipelines including data ingestion, training, evaluation, deployment, and monitoring on cloud infrastructure (e.g., AWS or equivalent).
• Integrate cloud-native and third-party AI SaaS solutions to accelerate delivery and reduce time to value.
• Ensure AI/ML solutions are scalable, dependable, secure, and cost-effective within cloud environments.
• Create reusable components, frameworks, and best practices to accelerate AI development.
• Evaluating emerging AI technologies including GenAI and agentic AI (e.g., Model Context Protocol (MCP), Google’s Agent-to-Agent (A2A) protocol), as well as third-party low-code platforms) for their feasibility, scalability, and alignment with cross-functional business needs.
• Solve for business problems by applying novel techniques and Innovating thinking.
• Partner with data scientists, architects, product managers, business stakeholders, and technical teams across the organization to ensure AI solutions align with organizational goals.
• Providing direct technical support and mentorship to technical teams across the enterprise is essential for enabling successful AI/ML implementations.
• Enabling other teams to adopt AI Into their products
• Leverage diverse skills and perspectives, leading to more effective problem-solving and decision-making.
• Other duties as assigned.

Benefits

• medical
• dental
• vision
• life and disability
• accident/critical illness/hospital
• well-being
• legal
• identity theft
• pet benefits
• Retirement
• paid time off/holidays
• leave
• incentive plans