Siemens Energy

A Snapshot of Your Day:

Join a forward-thinking team dedicated to harnessing the transformative power of AI within the energy sector. As an MLOps Engineer you will ensure that machine learning models are seamlessly integrated into workflow. You will proactively work with an existing AI Development team to design and deliver sophisticated, scalable, and resilient Generative AI based solutions on a Cloud Based platform.

How You’ll Make an Impact:

• Generative AI Application Development: Collaborate with developers and stakeholders in Agile teams to integrate LLMs and classical AI techniques into end-user applications, focusing on user experience, and real-time performance.
• End-to-End Pipeline Development: Build and maintain production-ready end-to-end ML pipelines, including data ingestion, preprocessing, training, evaluation, deployment, and monitoring; automate workflows using MLOps best practices to ensure scalability and efficiency. You are expected to be proficient in building and deploying models using AWS SageMaker and/or Azure ML Studio and able to monitor model performance, resource utilization and take corrective actions.
• Collaboration: Collaborate with data scientists and engineers to understand model requirements and optimize deployment processes.

What You Bring:

• Bachelor’s degree in computer science, Data Science, or a related field with a strong understanding of machine learning concepts and algorithms.
• 2+ years programming proficiency in Python with AI/ML libraries is a must.
• 2+ years of experience with cloud platforms like AWS and/or Azure and their respective machine learning services like but not limited to Amazon SageMaker and/or Azure ML Studio.
• 2+ years’ experience in FAST API development , relevant REST API development in C#, .NET will be considered.
• Familiarity with DevOps practices and tools (Docker, K8s, Git)
• Solid Understanding of software engineering principles and practices
• Working knowledge Vector Databases and generating Embeddings is an add-on
• Hands-on experience in machine learning frameworks like TensorFlow or PyTorch is good to have.
• Ability to provide support and guidance to cross functional teams in MLOps practices.

About the Team

Our Transformation of Industry division is decarbonizing the industrial sector. Increasing electrification and efficiency are key and demand for green H2 and derivative fuels will rise. We enable decarbonization of the industrial sector and the transition to sustainable processes, building on a strong industrial customer base, a global network, diverse technologies, and integrated execution capabilities. Candidates want to learn about the divisions they will be joining-the structure, how it works together, and the role it plays in driving Siemens Energy’s mission forward.

Who is Siemens Energy?

At Siemens Energy, we are more than just an energy technology company. With ~100,000 dedicated employees in more than 90 countries, we develop the energy systems of the future, ensuring that the growing energy demand of the global community is met reliably and sustainably. The technologies created in our research departments and factories drive the energy transition and provide the base for one sixth of the world's electricity generation.

Our distributed team is committed to making sustainable, reliable, and affordable energy a reality by pushing the boundaries of what is possible. We uphold a 150-year legacy of innovation that encourages our search for people who will support our focus on decarbonization, new technologies, and energy transformation.

Find out how you can make a difference at Siemens Energy: https://www.siemens-energy.com/employeevideo

Our Commitment to Diversity

Lucky for us, we are not all the same. Through diversity, we generate power. We run on inclusion and our combined creative energy is fueled by over 130 nationalities. Siemens Energy celebrates character – no matter what ethnic background, gender, age, religion, identity, or disability. We energize society, all of society, and we do not discriminate based on our differences.

Rewards/Benefits

• All employees are automatically covered under the Medical Insurance. Company paid considerable Family floater cover covering employee, spouse and 2 dependent children up to 25 years of age.
• Siemens Energy provides an option to opt for Meal Card to all its employees which will be as per the terms and conditions prescribed in the company policy.As a part of CTC, tax saving measure
• Flexi Pay empowers employees with the choice to customize the amount in some of the salary components within a defined range thereby optimizing the tax benefits. Accordingly, each employee is empowered to decide on the best Possible net income out of the same fixed individual base pay on a monthly basis.

https://jobs.siemens-energy.com/jobs