Staff Machine Learning Engineer

Responsibilities

• ML & AI System Development
• Design and build end-to-end ML pipelines, from data ingestion and feature engineering to model training, serving, and monitoring.
• Productionize AI agents, including LLM-backed workflows, multi-step tool use, and API orchestration.
• Collaborate with data scientists to bring experimental models into stable, high-performing production systems.
• MLOps & Infrastructure
• Implement and maintain MLOps workflows (CI/CD for ML), tracking experiments, managing model versions, and automating retraining.
• Set up observability for models and agents, including tracing, logging, latency/error tracking, and fallback logic.
• Ensure infrastructure supports scalability, performance, and compliance requirements.
• Technical Leadership & Collaboration
• Lead technical architecture for key AI and ML systems, ensuring maintainability and extensibility.
• Partner with product and platform teams to translate business needs into reliable and performant ML solutions.
• Mentor junior engineers and help elevate technical practices across the engineering org.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 8+ years of industry experience , with at least 4+ years in ML engineering or MLOps.
• Strong programming skills in Python and experience with ML libraries such as PyTorch , TensorFlow , and scikit-learn .
• Experience deploying AI agents in production, including retrieval-augmented generation (RAG), multi-step reasoning, and tool-use orchestration.
• Familiarity with LangChain , LlamaIndex , Haystack , or similar frameworks for agent development.
• Hands-on with LLMs (OpenAI, Anthropic, Cohere, etc.) , embedding models, and vector store integration.
• Expertise in MLOps tools like MLflow, Airflow, SageMaker, or Kubeflow.
• Experience with cloud platforms (preferably AWS), Docker/Kubernetes , and large-scale data systems (e.g., Snowflake, Databricks).
• Excellent problem-solving and system design skills, including CI/CD, testing, and infrastructure-as-code.
• Experience with streaming pipelines , online inference , and model monitoring at scale .
• Exposure to agent memory , feedback loops , or AI workflow orchestration in customer-facing products.
• Prior contributions to open-source ML or LLM projects are a plus.
• Why Join HG Insights?
• Work on high-impact AI products used by global enterprise customers.
• Lead the ML engineering strategy and shape our AI platform.
• Competitive compensation and benefits tailored for India-based employees.
• A collaborative and innovation-focused team environment.
• Ready to build the future of AI infrastructure? Apply now to join HG Insights as a Staff Machine Learning Engineer in Pune.

Additional Information

About HG Insights Headquartered in Santa Barbara, California, HG Insights is the global leader in technology intelligence. We help the world's most innovative companies accelerate their go-to-market efforts with precision through advanced data science methodologies and proprietary data assets. We offer a culture that blends innovation, collaboration, and growth, where each team member is empowered to make a measurable impact. Role Overview We are looking for a Staff/Senior Machine Learning Engineer to join our growing AI and Data Platform team in Pune, India . In this role, you will be responsible for designing, building, and scaling ML systems that power our core data intelligence products. You'll work at the intersection of data engineering and machine learning, collaborating closely with data scientists, software engineers, and product teams to turn models and agents into robust, production-ready systems. This is a high-impact role suited for someone who thrives on ownership, scalability, and deploying real-world ML and AI solutions at scale.

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