Lead Machine Learning Engineer

Overview

Lead Machine Learning Engineers at Thoughtworks use modern architectures to develop end-to-end scalable machine learning systems and applications. They use their specialized depth and breadth of knowledge to impact the achievement of client, project or service objectives and advocate for ways of working to promote and deliver excellence. They operate within the framework of functional policies, navigate through intricate challenges and apply their proficiency to contribute to the success of high-stakes projects.

Their leadership extends beyond technical prowess, encompassing strategic thinking and effective collaboration to drive innovation and deliver solutions that meet and exceed organizational goals.

As a lead machine learning engineer on projects, you will be leading the design of technical solutions or perhaps overseeing a program inception to build a new system and/or application. Alongside hands-on coding, as a key influencer, you will shape the trajectory of machine learning engineering initiatives, playing a pivotal role in advancing the field and ensuring impactful outcomes for the broader objectives of the company.

• You will embrace a strategic mindset, contributing to the direction of machine learning (ML) initiatives and aligning technical solutions with broader organizational goals.
• You will play a pivotal role in program inception, shaping the development of new systems and applications from idea to reality, overseeing technical feasibility and resource allocation.
• You will leverage your deep understanding of modern architectures to lead the development of scalable and maintainable ML systems, ensuring optimal performance and efficiency.
• You will translate client needs into technically feasible and impactful ML applications, driving solution design and deployment within complex, high-stakes projects.
• You will own the development and maintenance of ML applications, including ML pipelines, model training and deployment, and monitoring and evaluation.
• As a key influencer, you will champion Responsible AI and effective ways of working within the team, advocating for a culture of excellence and continuous improvement.
• You will navigate intricate technical challenges with proficiency, employing your specialized knowledge to troubleshoot issues and guide the team towards successful resolutions.
• You will stay at the forefront of the evolving field of machine learning, actively seeking out and implementing new technologies and advancements to ensure Thoughtworks remains a leader in innovation.
• You will foster a collaborative environment, effectively leading your team through hands-on coding alongside mentorship and guidance, empowering individual growth and knowledge sharing.
• You will measure and analyze the impact of ML initiatives, iteratively refining approaches and ensuring solutions deliver tangible value to clients and the organization.

• You have experience in developing a technical vision and strategy, keeping it relevant and aligned to the business needs.
• You can design and execute cross-functional requirements based on business priorities.
• You have experience in writing clean, maintainable and testable code, demonstrating attention to refactoring and readability of the code using Python or Shell.
• You have experience with distributed systems and scalable architectures to handle large-scale ML applications.
• You have experience with building, deploying and maintaining ML systems using relevant ML techniques and platforms, i.e.:
  Scikit-learn, Tensorflow, MLFlow, Kubeflow, Pytorch.
• You have experience with building, deploying and maintaining ML systems and experience with application of MLOps principles and CI/CD to ML.
• You have experience in machine learning engineering and data science, are familiar with key ML concepts, algorithms and frameworks, and understand ML model life cycles.
• You have experience with designing and operating the infrastructure required to run different types of ML training and serving workloads, i.e.: on-premise vs. cloud infrastructure, infrastructure as code, monitoring, etc.
• You have hands-on experience with…