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AI / Machine Learning Engineer

AI / Machine Learning Engineer

Siemens Energygurugram, India
17 hours ago
Job description

AI / Machine Learning Engineer

About the Role

Location India Haryana Gurugram Company Siemens Energy Industrial Turbomachinery India Private Limited Organization EVP Global Functions Business Unit Digital Products and Solutions Full / Part time Full-time Experience Level Experienced Professional

A Snapshot of Your Day

We are seeking a skilled AI / Machine Learning Engineer to join our team and help build innovative machine learning solutions that drive business outcomes. You will collaborate with multi-functional teams including data scientists, software engineers, and product managers to design, develop, and maintain robust machine learning models and workflows. Your work will involve transforming raw data into actionable insights, optimizing algorithms for performance, and integrating AI capabilities into dynamic applications to provide seamless user experiences and enhanced functionality !

How You’ll Make an Impact

  • Create end-to-end workflows for the training and inference pipeline of the machine learning models.
  • Responsible for designing, developing, and implementing multi-step RAG (Retrieval-Augmented Generation), agentic, or tool-augmented workflows using Python and frameworks like LangChain and LangGraph.
  • Know the latest advancements in agentic AI, large language model (LLM) orchestration, and tools within the Python ecosystem.
  • Build and optimize RAG pipelines using vector stores such as FAISS, AWS OpenSearch.
  • Implement solutions for processing and analyzing time series data using libraries like Pandas and NumPy, enhancing data-driven decision-making.
  • Write, evaluate, and optimize prompts for LLMs to improve the accuracy and efficiency of AI-driven applications.
  • Collaborate with other developers to create, deploy, and maintain applications for different platforms.
  • Write and review code for multiple applications, ensuring high quality and readability.
  • Conduct unit testing and integration analysis to refine product performance.
  • Ensure consistency between delivered product features and business requirements.
  • Optimize application performance and resolve issues across different platforms.

What You Bring

  • You hold a Bachelor’s degree in Computer Science, Information Technology, Software Engineering, or a related field.
  • Proven 3+ years of experience as a Machine Learning Engineer or AI Developer in building complex AI-driven applications.
  • Proficient programming experience in Python, with hands-on knowledge of libraries such as scikit-learn, Numpy, Pandas, Langchain, LangGraph, TensorFlow, or PyTorch.
  • Familiarity with building APIs (Application Programming Interfaces) and integrating third-party libraries.
  • Understanding of AWS services for deploying FastAPI applications (, Lambda, S3, ECS, SageMaker, StepFunctions) or Basic understanding of the Azure services.
  • Familiarity with the Agile development lifecycle.
  • Knowledge of version control tools such as Git and CI / CD processes using Jenkins or similar tools.
  • Strong problem-solving and critical-thinking abilities.
  • Strong communication skills to support engagement with various collaborators.
  • Ability to work under pressure and adhere to tight deadlines.
  • Capability to switch between different projects as needed (, application development vs. AI / ML Research).
  • Experience with backend integrations relevant to machine learning applications and data pipelines, such as AWS services (, SageMaker, Lambda, S3, Step Function) or other cloud-based platforms (Azure).
  • Understanding of standard methodologies for deploying and managing AI / ML models in production environments.
  • Understanding of time series analysis techniques and familiarity with handling time-dependent data using libraries such as Sklearn, Pandas and NumPy, along with knowledge of leveraging LLMs for various natural language processing tasks and user interactions in AI applications.
  • Prior experience with model testing and validation frameworks (, MLflow, Pytest for Python) to ensure the robustness and reliability of machine learning solutions.
  • Proficiency in data engineering practices, including data wrangling, cleaning, and preprocessing for machine learning tasks.
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