AI/Machine Learning Engineer

The typical interview experience for an AI/Machine Learning Engineer at Siemens Energy includes an online assessment covering logical reasoning, quantitative aptitude, and Python coding. The technical interview dives deep into machine‑learning fundamentals, model building, evaluation metrics, and hands‑on coding on data‑preprocessing and deployment. An HR round follows to assess cultural fit, communication skills, and career aspirations. Preparation tips: revise core ML algorithms, practice Python coding on platforms like LeetCode, and be ready to discuss any projects or internships in detail.

Siemens Energy fosters a collaborative and inclusive environment where innovation is encouraged. Employees benefit from continuous learning programs, mentorship, and a transparent career ladder from Engineer to Senior and Principal roles. Flexible timings and remote‑work options support a healthy work‑life balance.

Bachelor's degree in Computer Science, Information Technology, Electronics & Communication, or related engineering streams with a minimum of 60% aggregate (or CGPA 6.5/10). Final year students of the 2025, 2026 or 2027 batches are eligible. No active backlogs at the time of joining. Strong academic record and demonstrable projects or internships in AI/ML, NLP, or data analytics are required.

Round 1: Online aptitude & coding test → Round 2: Technical interview (ML concepts, coding, system design) → Round 3: HR interview (fitment, motivations)

Siemens Energy is a global leader in energy technology, employing nearly 100,000 people across more than 90 countries. The company designs, manufactures, and services a wide range of products and solutions that enable the transition to a sustainable energy future. With a legacy of over 150 years of innovation, Siemens Energy drives the development of renewable power, grid technologies, and digital solutions that power one‑sixth of the world’s electricity generation. Its commitment to decarbonisation, digitalisation, and reliable energy makes it an attractive destination for fresh talent eager to contribute to large‑scale impact. The AI/Machine Learning Engineer role sits within the Digital Products and Solutions business unit of Siemens Energy Industrial Turbomachinery India Private Limited. Reporting to the EVP Global Functions, the engineer will work closely with data scientists, software engineers, and product managers to create end‑to‑end machine‑learning pipelines that turn raw data into actionable insights. The position is based in Gurgaon, Haryana, and offers a full‑time, entry‑level opportunity for recent graduates or candidates with up to three years of experience. Key responsibilities: 1. Assist in building and maintaining ML and basic Generative AI pipelines covering data preprocessing, model training, evaluation, and inference. 2. Support the development of simple Retrieval‑Augmented Generation (RAG) and NLP workflows under senior guidance. 3. Perform text‑processing tasks such as cleaning, parsing, chunking, and generating embeddings. 4. Develop and expose backend APIs (e.g., FastAPI) to deliver ML/AI functionalities to applications. 5. Help integrate AI models into product features and assist with deployment activities on cloud platforms. 6. Write clean, modular, and testable Python code following industry best practices. 7. Collaborate with cross‑functional teams to deliver features on schedule. 8. Debug, test, and optimise models and pipelines for performance, scalability, and reliability. 9. Stay updated with the latest advancements in AI/ML and Generative AI and propose improvements. 10. Document work, create knowledge‑share sessions, and mentor junior team members. Tech stack includes Python, NumPy, Pandas, scikit‑learn, PyTorch/TensorFlow, FastAPI, RESTful services, Git, and basic cloud services (AWS/Azure). The role offers a clear growth path: starting as an Engineer, progressing to Senior Engineer, then to Lead/Principal Engineer, with opportunities to move into product management or solution architecture. Joining Siemens Energy provides exposure to cutting‑edge energy projects, a culture that values diversity and inclusion, robust learning programs, and the chance to contribute to a sustainable future while building a rewarding career.