Senior ML Engineer

Job Description:

Are you interested in empowering Arm’s engineering teams to create products using the power of machine learning and statistics? Are you passionate about working in a team that thrives on creativity, innovation, and diversity?

Arm is using Machine Learning and Data Science techniques to empower our engineers to make data-driven decisions and is building automated workflows that enable our engineers to deliver more complex products. Based in the “Machine Learning for Verification” (ML4V) team in Arm’s Productivity Engineering group, this role will enable you to directly impact Arm’s engineering processes and will help improve future generations of Arm-based technology used by 70% of the world’s population.

As a Senior ML Engineer, you will be working across Arm engineering workflows ensuring that our solutions are optimized and delivering maximum value. You will be part of a highly interdisciplinary team that deliver compute, data science, research, and engineering. You will be responsible for productizing data pipelines and models and deploying them into a production environment so that they deliver the maximum value to our teams. Because we have such a diverse team, with many areas of speciality, there will be opportunities to mentor and coach, as well as to develop your own knowledge and understanding.

Our technical stack leverages open-source python libraries, using distributed compute across on-prem and cloud environments.

Responsibilities:

• Building and optimising ML processes across the whole ML lifecycle, from proof-of-concept to production
• Writing and deploying scalable and resilient solutions
• Collaborating with our diverse teams including Verification engineers and data scientists
• Communicating your work to technical and non-technical collaborators.

Required Skills and Experience:

• Demonstrable experience using python to deploy and run machine learning processes in a production environment.
• Demonstrable knowledge of statistics and machine learning (eg, Dimensionality Reduction, Hypothesis Testing, Imputation, Clustering methods, Tree Based Algorithms, Neural Networks)
• Experience with Data Science and Machine Learning Frameworks (e.g Pandas, Scikit-Learn)
• Experience with Cloud platforms like AWS, GCP, Azure.
• Experience with software development & CI/CD processes: (Git, testing, releasing code)
• Comfortable working within a Linux environment

“Nice To Have” Skills and Experience:

• A master or PhD degree in a relevant field, such as computer science, physics, statistics, maths etc
• Experience working with imbalanced datasets.
• Experience with distributed compute using pyspark
• Experience with Databases (no-sql, sql)
• Experience serving models through a service orientated architecture
• Experience with Serving ML models in a streaming environment.
• Experience mentoring and/or coaching colleagues.