Arm is seeking an AI/ML Ops + Developer Engineer to build, train, and deploy ML models in real-world environments, leveraging software engineering, semiconductor engineering, machine learning, and scalable deployment expertise.
Requirements
- Hands-on experience with building, training, evaluating, and deploying ML/DL models using modern frameworks (e.g., PyTorch, TensorFlow, Scikit-learn, XGBoost)
- Practical understanding of ML lifecycle orchestration using tools such as MLflow, SageMaker, or custom pipelines
- Experience with structured and unstructured data ingestion, feature engineering, and pipeline construction using Python, SQL, and cloud-native tools (e.g., AWS Lambda, S3, DynamoDB)
- Proficiency in Python; familiarity with R, C++, or Java/Scala is a plus
- Exposure to containerization (Docker), REST API development, and deploying models to production environments
- Fluency with GIT for collaborative development and code management
- Exposure to large language models (e.g., OpenAI APIs, HuggingFace), prompt engineering, fine-tuning, or RAG pipelines using LangChain or similar frameworks
Responsibilities
- Building, training, evaluating, and deploying ML/DL models using modern frameworks (e.g., PyTorch, TensorFlow, Scikit-learn, XGBoost)
- ML lifecycle orchestration using tools such as MLflow, SageMaker, or custom pipelines
- Data ingestion, feature engineering, and pipeline construction using Python, SQL, and cloud-native tools (e.g., AWS Lambda, S3, DynamoDB)
- Deploying models to production environments using containerization (Docker) and REST API development
- Collaborative development and code management using GIT
- Working with large language models (e.g., OpenAI APIs, HuggingFace), prompt engineering, fine-tuning, or RAG pipelines using LangChain or similar frameworks
- Applying time-series forecasting techniques (ARIMA, LSTM), regression modeling, and statistical inference
Other
- BS or MS or PhD in Data Science, Computer Science, Engineering, or related technical field
- Internship or full-time experience in applied ML roles across industry or research
- A portfolio of ML applications or publications showing real-world problem-solving capability
- Ability to work in a hybrid environment with flexible working patterns
- Commitment to Arm's 10x mindset and values
