Sr. Machine Learning Engineer

Overview

Your Role At A Glance

Mastercam is expanding its AI capabilities by developing product-grade Copilot experiences and next-generation automation workflows that operate inside and alongside the core Mastercam application. We are seeking a highly experienced Senior Machine Learning Engineer to design and deliver robust AI integrations that help users complete real CAM tasks more efficiently, safely, and consistently. This role requires deep ML/DL modeling, agentic AI solutioning, and production-grade deployment of AI systems integrated into a large-scale C++ CAM application.

This role focuses on shipping production software, not research for research’s sake. You will build the engineering foundation for agentic workflows (tools, orchestration, automation, guardrails), integrate with cloud-based AI services (Azure-first today), and help evolve our approach from prompt-centric solutions toward scalable, maintainable systems that learn from usage signals and enable smarter recommendations over time. This is a hands-on technical leadership role, requiring the ability to take AI solutions from concept to cloud-deployed production systems.

*Must be located in the Pune area*

How You’ll Drive Success

ML / DL Modeling & Applied AI

• Design, develop, and optimize machine learning and deep learning models using Python-based frameworks such as scikit-learn, TensorFlow, PyTorch, etc.
• Apply ML/DL techniques to solve real-world problems in CAD/CAM and manufacturing workflows.
• Perform feature engineering, model evaluation, validation, and performance optimization.
• Translate research ideas and prototypes into robust, production-ready AI solutions.

Agentic AI & AI Solutioning

• Design and implement agentic AI workflows using commercial and open-source AI toolkits.
• Build proof-of-value (PoV)solutions rapidly using:
• LLMs
• Multi-agent systems
• Tool-using and orchestrated agents
• Maintain strong awareness of the AI tooling ecosystem, including:
• Agent frameworks
• LLM platforms
• Vector databases
• Orchestration and observability tools
• Evaluate and recommend architectures, tools, and frameworks suitable for enterprise-scale AI systems.

End-to-End Product Integration

• Build end-to-end AI solutions, from ideation and experimentation to deployment and long-term maintenance.
• Integrate ML/AI capabilities into production-grade C++ applicationsthat form part of the Mastercam product. Design, build, and maintain production-grade AI integrations within Mastercam, including Copilot-style experiences and workflow automation capabilities.Design hybrid architectures involving:
• Desktop/on-prem software
• Cloud-hosted AI services
• Collaborate closely with product, platform, and core engineering teams to ensure performance, scalability, and reliability.
• Develop backend services and APIs that connect the Mastercam application to cloud AI services (Azure-first), internal systems, and external tooling.
• Build reliable agentic workflows that orchestrate tools and actions safely, including permissions/scoping, guardrails, audit logging, retries/recovery, and human-in-the-loop patterns when appropriate.
• Implement robust observability for AI features (telemetry, tracing, quality signals, latency/cost metrics) to support continuous improvement and operational reliability.
• Establish and follow engineering best practices (code quality, automated testing, CI/CD, secure development practices) for AI-enabled services and integrations.
• Partner with ML/AI specialists (internal or external) to integrate LLM capabilities (prompting, structured outputs, retrieval/RAG, tool calling) into user-facing product features.
• Drive technical decision-making by evaluating tradeoffs among approaches (prompting vs retrieval vs rules/tools vs targeted models) with emphasis on maintainability, cost, latency, and user safety.
• Contribute to technical documentation, system diagrams, runbooks, and knowledge sharing to ensure long-term maintainability and team scalability.
• Participate in code reviews, incident response, and on-call/support rotations as required to ensure dependable delivery and uptime of AI-related services.

Cloud Deployment & MLOps

• Design, deploy, and operate production-grade AI/ML systems on cloud platforms (Azure preferred)
• Own the complete AI lifecycle, including:
• Model packaging and deployment
• Versioning and experiment tracking
• Monitoring, alerting, and retraining
• Implement MLOps best practices, including:
• CI/CD pipelines for ML models
• Automated testing and validation
• Ensure AI systems meet enterprise requirements for:
• Scalability
• Reliability
• Security
• Cost efficiency
• Partner with infrastructure and DevOps teams to operationalize AI solutions.

The Talents We’re Seeking

Education & Experience

• Bachelors in Mechanical/Industrial Engineering with Masters in AI/ML from reputed institutes like IIT, BITS, NIT or equivalent global institutions.
• 10+ years of professional experience delivering software and/or machine learning solutions to production.
• Strong applied ML background with proven ability to deliver product outcomes(not research-only), including:
• Problem framing, data requirements, experimentation, and iteration.
• Model evaluation, deployment, monitoring, and operational ownership.
• Hands-on experience integrating LLMs into products, including at least several of:
• Prompting and structured outputs
• Tool/function calling
• Retrieval/RAG and embeddings
• Evaluation methods to measure quality and prevent regressions
• Ability to choose the right approach per use case (and explain tradeoffs): prompting vs RAG vs fine-tuning vs small dedicated models vs rule/tool-based automation.
• Practical experience building lightweight ML models for limited-scope decision-making (e.g., classifiers/rankers) under constraints (latency, cost, maintainability).
• Strong hands-on experience with cloud ML platforms, preferably Microsoft Azure (current primary provider), including some of:
• Training pipelines, model packaging, deployment, monitoring, cost/latency management.
• Strong engineering fundamentals: API/service integration, code quality, testing mindset, and collaborative development practices.
• Practical experience building reliable and safe automation, including guardrails such as:
• Permissions/scoping, auditability, traceability, rate limiting, retry/recovery, and human-in-the-loop patterns.
• Experience with MCP (Model Context Protocol) and/or designing tool ecosystems for agentic workflows.

Required Skills

• Experience with small/task-specific models (fine-tuning or training lightweight models) and knowing when they outperform general-purpose LLMs (cost/latency/privacy).
• Familiarity with multiple ML/LLM ecosystems beyond Azure (e.g., Hugging Face, AWS, open-source model serving).
• Experience designing feedback loops from product telemetry/user signals to improve automation over time (evaluation harnesses, offline/online metrics, regression testing).
• Domain familiarity with manufacturing/CAM software, automation tooling, or complex desktop applications is a plus

Who We Are

At Mastercam, we do not just keep pace with manufacturing—we set the pace. For over 40 years, we have been the name behind the breakthroughs, the partner for those who refuse to settle. When the industry says “too complex,” we say, “challenge accepted.”

We are more than software. We are a movement of makers, innovators, and problem-solvers driving transformation across the globe.

Backed by a network of 400 Channel Partners and a thriving developer community, Mastercam delivers the tools and expertise to turn ambitious ideas into flawless reality. From aerospace to automotive, medical to education, we empower manufacturers to push boundaries and redefine what is possible.

As part of Intelligent Manufacturing and the Sandvik Group, we are leading the charge in digital transformation. Our team of 350+ professionals is united by a single mission: to help achieve precision, productivity, and performance without compromise.

Our Core Values? They are not just words. They are how we win:

• Winning Together: Collaboration is not optional—it is the engine that drives us.
• Curiosity: We question, we explore, we innovate. Every day.
• Responsibility: Safety, integrity, and sustainability aren’t boxes to check—they are the foundation of trust.
• Customer-Focused: We listen. We adapt. We deliver. Always.

Innovation. Collaboration. Growth. That is the Mastercam way. Explore more at www.mastercam.com, connect on LinkedIn, and join the conversation with #mastercam.

The next big challenge is waiting—are you ready to accept?

It is the policy of the company to provide equal employment opportunities to all employees and employment applicants without regard to race, color, religion, sex, or national origin or any other classification protected by applicable local or state laws.

EOE/M/F/Vet/Disabled are encouraged to apply.

We are an E-Verify Employer.