Principal Machine Learning Engineer

Thoughtworks•Chicago, IL

1d•$245,000 - $393,000•Remote

About The Position

Principal 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 Principal 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.

Requirements

Experience in developing a technical vision and strategy, keeping it relevant and aligned to the business needs.
Ability to design and execute cross-functional requirements based on business priorities.
Experience with distributed systems and scalable architectures to handle large-scale ML applications.
Experience in machine learning engineering and data science, familiar with key ML concepts, algorithms and frameworks, and understanding ML model lifecycles.
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.
Understanding the importance of stakeholder management and ability to liaise between clients and other key stakeholders throughout projects, ensuring buy-in and gaining trust.
Resilience in ambiguous situations and ability to adapt role to approach challenges from multiple perspectives.
Willingness to take on and skillfully manage risks or conflicts.
Eagerness to coach, mentor and motivate others and aspiration to influence teammates to take positive action and accountability for their work.
Enjoy influencing others and advocating for technical excellence while being open to change when needed.
Proven leadership with a track record of encouraging teammates in their professional development and relationships.
Natural ability to cultivate strong partnerships and understanding the importance of relationship building and how it can bring new opportunities to the business.

Responsibilities

Embrace a strategic mindset, contributing to the direction of machine learning (ML) initiatives and aligning technical solutions with broader organizational goals.
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.
Leverage deep understanding of modern architectures to lead the development of scalable and maintainable ML systems, ensuring optimal performance and efficiency.
Translate client needs into technically feasible and impactful ML applications, driving solution design and deployment within complex, high-stakes projects.
Own the development and maintenance of ML applications, including ML pipelines, model training and deployment, and monitoring and evaluation.
As a key influencer, champion Responsible AI and effective ways of working within the team, advocating for a culture of excellence and continuous improvement.
Navigate intricate technical challenges with proficiency, employing specialized knowledge to troubleshoot issues and guide the team towards successful resolutions.
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.
Foster a collaborative environment, effectively leading your team through hands-on coding alongside mentorship and guidance, empowering individual growth and knowledge sharing.
Measure and analyze the impact of ML initiatives, iteratively refining approaches and ensuring solutions deliver tangible value to clients and the organization.