ML Engineer

Job ID

Date posted
14/10/2025
Location
Bengaluru, India
Category
IT

Job Overview
We are looking for a Machine Learning Engineer / Data Scientist to drive the improvement, evaluation, and optimization of our AI solutions. This role will focus on model development, fine-tuning, and evaluation, ensuring our AI applications and intelligent agents perform at the highest levels of accuracy, efficiency, and reliability.

You will collaborate closely with AI Developers to integrate your optimized models into production systems. Work closely with business stakeholders to define meaningful success metrics. The role blends hands-on engineering with data science experimentation, making it ideal for someone passionate about improving real-world AI solutions.

Responsibilities

• Fine-tune, optimize, and retrain ML/AI models.
• Build and maintain evaluation pipelines to test accuracy, robustness, fairness, and efficiency.
• Automate ML workflows and lifecycle management.
• Access and prepare high-quality datasets for training and evaluation.
• Perform light feature engineering and data transformations needed for model optimization.
• Implement monitoring and feedback loops to track model performance post-deployment.
• Conduct benchmarking and A/B testing to validate model improvements.
• Work with Databricks Mosaic AI and cloud ML services (Azure ML, AWS SageMaker) for scalable workloads.

Required Skills And Experience

• Experience (4 to 8 Years), Proven background in machine learning engineering and MLOps practices.
• Proficiency in Python with ML/AI frameworks such as PyTorch, TensorFlow, scikit-learn.
• Hands-on experience with MLflow for model tracking, deployment, and lifecycle management.
• Experience fine-tuning LLMs or training traditional ML models.
• Familiarity with evaluation frameworks (DeepEval, RAGAS, custom pipelines).
• Strong SQL skills and ability to work with structured/unstructured datasets.
• Exposure to Spark/Databricks for data processing.
• Understanding of Deep Learning and Neural Network architectures.
• Experience with cloud ML platforms (Azure, AWS).

"Nice To Have" Skills And Experience

• Familiarity with LangChain/LangGraph evaluation and testing tools.
• Experience with vector databases (Pinecone, FAISS, Weaviate, Chroma).
• Knowledge of bias, fairness, and explainability tools (SHAP, LIME, InterpretML).
• Awareness of modern ML benchmarks (HELM, MMLU) for LLM evaluation.

In Return
Our
10x mindset
guides how we engineer, collaborate, and grow. Understand what it means and how to reflect 10x in your work:
Our 10x Mindset Guides How We Engineer, Collaborate, And Grow. Understand What It Means And How To Reflect 10x In Your Work

Accommodations at Arm
At Arm, we want to build extraordinary teams. If you need an adjustment or an accommodation during the recruitment process, please email

Hybrid Working at Arm
Arm's approach to hybrid working is designed to create a working environment that supports both high performance and personal wellbeing. We believe in bringing people together face to face to enable us to work at pace, whilst recognizing the value of flexibility. Within that framework, we empower groups/teams to determine their own hybrid working patterns, depending on the work and the team's needs. Details of what this means for each role will be shared upon application. In some cases, the flexibility we can offer is limited by local legal, regulatory, tax, or other considerations, and where this is the case, we will collaborate with you to find the best solution. Please talk to us to find out more about what this could look like for you.

Equal Opportunities at Arm
Arm is an equal opportunity employer, committed to providing an environment of mutual respect where equal opportunities are available to all applicants and colleagues. We are a diverse organization of dedicated and innovative individuals, and don't discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.