Senior Machine Learning Engineer

Overview

Senior Machine Learning Engineer role at Thoughtworks. The Senior ML Engineer builds, maintains and tests the architecture and infrastructure for managing machine learning applications. They support and contribute to the design of end-to-end applications and products, and are responsible for building core capabilities including technical and functional ML systems, acting as the anchor for functional streams of work with accountability for timely delivery.

As a senior machine learning engineer, you will work on the latest tools, frameworks and offerings while enabling credible and collaborative problem solving to execute on a strategy.

Responsibilities

• Contribute to design and drive the development of robust scalable architectures and infrastructure for deploying and managing machine learning (ML) applications, ensuring high availability, performance and security.
• Collaborate with data scientists and engineers to translate business needs into effective and efficient ML systems and applications.
• Own the development and maintenance of core functionalities within ML applications, including ML pipelines, model training and deployment, and monitoring and evaluation.
• Drive the functional stream of work by providing technical expertise, leading team discussions and ensuring timely delivery of assigned tasks.
• Stay ahead of the curve by actively exploring and implementing the latest tools, frameworks and offerings in the ML landscape.
• Facilitate collaborative problem solving within the team by actively listening, communicating effectively and mentoring other engineers.
• Contribute to the development and execution of the team\'s overall ML strategy, aligning technical capabilities with business objectives.
• Proactively identify and address challenges related to ML systems and applications, proposing solutions and implementing improvements.

Qualifications

• Strong experience with LLM and AI; proficient in Python or Shell; strong focus on clean, maintainable and testable code.
• Advanced English level.
• Experience with distributed systems and scalable architectures to handle large-scale ML applications.
• Experience building, deploying, and maintaining ML systems using Scikit-learn, TensorFlow, MLFlow, Kubeflow, PyTorch, and related tools.
• Experience with MLOps principles and CI/CD for ML projects.
• Familiarity with ML concepts, algorithms, frameworks and ML model lifecycles.
• Experience designing and operating the infrastructure required to run different ML training and serving workloads (on-premise vs cloud, infrastructure as code, monitoring).
• Hands-on experience with on-premise and cloud services for ML pipelines (Azure, AWS, GCP or Databricks and related ML managed services).

Professional Skills

• Stakeholder management and ability to liaise between clients and key stakeholders to gain buy-in and trust.
• Resilience in ambiguous situations and adaptability to changing challenges.
• Willingness to take on risks or conflicts and manage them effectively.
• Mentoring, motivating others and influencing teammates to take accountability for their work.
• Advocacy for technical excellence and openness to change when needed.

Other things to know

Learning & Development: Thoughtworks supports career development with interactive tools, development programs and a culture of growth. Your career path can be shaped by you, within the culture of collaboration and support.

About Thoughtworks: Thoughtworks is a dynamic and inclusive technology consultancy driving impact by solving complex business problems with technology. For 30+ years we\'ve delivered extraordinary impact together with clients. Bring your expertise and commitment to continuous learning to Thoughtworks. Let\'s be extraordinary together.

See here our AI policy.

Seniority level

• Not Applicable

Employment type

• Full-time

Job function

• Engineering and Information Technology
• Industries: Software Development and IT Services and IT Consulting

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