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Siemens
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AI/ML Engineer

AI/ML Engineer

Siemens

4 - 6 years

11 - 15 Lacs

bengaluru

Posted:10 hours ago| Platform:

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Skills Required

python version control artificial intelligence tensorflow software engineering natural language processing scikit-learn microsoft azure numpy machine learning docker pandas git spark gcp computer vision pytorch keras hadoop agile aws big data ml

Work Mode

Work from Office

Job Type

Full Time

Job Description

We are looking for

AI/ML Engineer

Before our software developers write even a single line of code, they have to understand what drives our customers. What is the environment? What is the user story based on? Implementation means trying, testing, and improving outcomes until a final solution emerges. Knowledge means exchange discussions with colleagues from all over the world.

Join our Digitalization Technology and Services (DTS) team based in Bangalore.

Youll make a difference by:

Developing, training, and deploying machine learning models to solve real-world problems.

Designing and implementing scalable AI/ML pipelines, from data preprocessing to model deployment.

Collaborating with data engineers and backend teams to integrate models into production systems.

Optimizing algorithms and models for performance, accuracy, and efficiency.

Conducting exploratory data analysis to uncover insights and inform model development.

Staying abreast of the latest AI/ML advancements and apply them to enhance project outcomes.

Troubleshooting and refining models with minimal guidance, ensuring robustness and reliability.

Job Requirements/ Skills:

4-6 years of experience in AI/ML development, with a focus on practical applications.

Strong proficiency in Python and libraries such as TensorFlow, PyTorch, scikit-learn, or Keras.

Experience with data manipulation tools (e.g., Pandas, NumPy) and working with large datasets.

Knowledge of supervised and unsupervised learning techniques, NLP, or computer vision (depending on project needs).

Familiarity with cloud platforms (e.g., AWS, GCP, Azure) for model training and deployment.

Ability to work independently, prioritize tasks, and deliver high-quality results with minimal oversight.

Solid understanding of software engineering principles and version control (e.g., Git).

Excellent analytical skills and a strong foundation in statistics and mathematics.

Preferred Qualifications:

Experience with MLOps tools (e.g., MLflow, Kubeflow) or containerization (e.g., Docker).

Familiarity with big data frameworks like Spark or Hadoop.

Prior work in deploying AI models in production environments or real-time systems.

Exposure to Agile methodologies or cross-functional team settings.

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AI/ML Engineer