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Thoughtworks

Thoughtworks is a dynamic and inclusive community of bright and supportive colleagues who are revolutionizing tech. As a leading technology consultancy, we’re pushing boundaries through our purposeful and impactful work. Over 30 years of delivering extraordinary impact with clients. Helping clients solve complex business problems with technology as the differentiator.

Lead Machine Learning Engineer

EngineerEngineerFull TimeRemoteLeadTeam 10,001

Location

Worldwide

Posted

4 days ago

Salary

C$156K - C$251K / year

Seniority

Lead

Job Description

Lead Machine Learning Engineer

Thoughtworks

Role Description 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. Job 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 your 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. - 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 your 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. Qualifications - 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 in writing clean, maintainable and testable code, demonstrating attention to refactoring and readability of the code using Python. - Experience with distributed systems and scalable architectures to handle large-scale ML applications. - Experience with building, deploying and maintaining ML systems using relevant ML techniques and platforms, i.e.: Scikit-learn, Tensorflow, MLFlow, Kubeflow, Pytorch. - Experience with application of MLOps principles and CI/CD to ML. - Experience in machine learning engineering and data science, familiar with key ML concepts, algorithms and frameworks, and understand 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. - Hands-on experience with on-premise and cloud services for building and deploying ML pipelines, i.e.: Azure, AWS, GCP and/or Databricks and associated ML managed services. Professional Skills - Understanding 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 your role to approach challenges from multiple perspectives. - Willingness to take on risks or conflicts and manage them skillfully. - Eagerness to coach, mentor and motivate others, aspiring to influence teammates to take positive action and accountability for their work. - Enjoyment in 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 understand the importance of relationship building for new opportunities. Benefits - Learning & Development: Career development supported by interactive tools, numerous development programs, and teammates who want to help you grow. - Responsible Use of AI in Recruitment: AI tools are used to support recruitment with administrative tasks, ensuring fairness and responsible AI. - Accommodations: Commitment to providing reasonable accommodations to qualified applicants with disabilities or sincerely held religious beliefs. - Cancellations: Awareness that project scope or availability may shift or be cancelled during the recruitment and selection process. Salary $156,000 — $251,000 CAD

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