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 - 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. Job qualifications Technical Skills - 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. - 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 lifecycles. - 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 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 - You understand the importance of stakeholder management and can easily liaise between clients and other key stakeholders throughout projects, ensuring buy-in and gaining trust along the way. - You are resilient in ambiguous situations and can adapt your role to approach challenges from multiple perspectives. - You don’t shy away from risks or conflicts, instead you take them on and skillfully manage them. - You are eager to coach, mentor and motivate others and you aspire to influence teammates to take positive action and accountability for their work. - You enjoy influencing others and always advocate for technical excellence while being open to change when needed. - You are a proven leader with a track record of encouraging teammates in their professional development and relationships. - Cultivating strong partnerships comes naturally to you; You understand the importance of relationship building and how it can bring new opportunities to our business. Other things to know Learning & Development There is no one-size-fits-all career path at Thoughtworks: however you want to develop your career is entirely up to you. But we also balance autonomy with the strength of our cultivation culture. This means your career is supported by interactive tools, numerous development programs and teammates who want to help you grow. We see value in helping each other be our best and that extends to empowering our employees in their career journeys. Responsible Use of AI in Recruitment At Thoughtworks, we use AI tools to support our recruitment team with administrative tasks such as drafting communications, scheduling interviews and writing job descriptions. Crucially, our AI tools do not screen, assess, rank or make hiring decisions. Every application is reviewed by our team and all selection decisions are made exclusively by our interviewers and hiring managers. We are committed to fairness and responsible AI. We actively manage our AI systems by testing, monitoring for biased outcomes and implementing mitigation measures. We hold our third-party vendors to these same high standards through a rigorous governance process. For additional information, please see our full Thoughtworks AI Policy for Recruitment. EEO Thoughtworks is an equal-opportunity employer. We are committed to providing equal employment opportunities to all qualified applicants and employees without regard to race, color, religion, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender identity or expression, national origin, ancestry, age, disability, genetic information, marital status, military or veteran status, or any other characteristic protected by applicable federal, state, or local law. We prohibit discrimination and harassment of any kind and are dedicated to providing a work environment free from discrimination and harassment. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, stermination, layoff, recall, transfer, leaves of absence, compensation, and training. Thoughtworks is also an affirmative action employer of veterans and individuals with disabilities. For additional information, please see the Thoughtworks, Inc. Equal Employment Opportunity & Affirmative Action Policy Statement. US - Work Authorization Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment in the United States. Accommodations Thoughtworks is committed to providing reasonable accommodations to qualified applicants with disabilities or sincerely held religious beliefs, practices, or observances, in accordance with applicable law. If you need a reasonable accommodation to complete any part of the application process, participate in interviews, or otherwise engage in the hiring process, you may request an accommodation by completing this form or speaking with your recruiter. Requests may be made at any stage of the application or interview process. Once a request is received, Thoughtworks will engage in an interactive process with the applicant to determine an appropriate accommodation. Applicants are not required to disclose medical diagnoses or detailed personal information in order to request an accommodation. All accommodation requests will be handled in a timely, confidential, and respectful manner, consistent with applicable legal requirements. Requesting an accommodation will not negatively affect your consideration for employment. Company prohibits retaliation against any applicant for requesting an accommodation or participating in the accommodation process. Accommodations made during the recruitment process are not a guarantee of future or continued accommodations once hired. If you are hired by Thoughtworks, and require an accommodation to perform the essential functions of your role, you may be asked to engage in our reasonable accommodation process. Cancellations As a technology consultancy, the projects we undertake are subject to change based on client needs and agreements. While we strive for consistency, please be aware that project scope or availability may shift, or projects may even be cancelled, during the recruitment and selection process, which is often outside of our direct control. Should the project related to this vacancy be significantly altered or cancelled, all impacted candidates will be promptly and duly informed of the change About 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. For 30+ years, we’ve delivered extraordinary impact together with our clients by helping them solve complex business problems with technology as the differentiator. Bring your brilliant expertise and commitment for continuous learning to Thoughtworks. Together, let’s be extraordinary. #LI-Remote Salary Benefits: https://www.thoughtworks.com/en-us/careers/benefits The annual salary range posted is subject to many factors and may vary depending on experience, geographic location, job responsibilities, performance, skills and/or training. Salary $172,000—$276,000 USD See here our AI policy.

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 - 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. Job qualifications Technical Skills - 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. - 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 lifecycles. - 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 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 - You understand the importance of stakeholder management and can easily liaise between clients and other key stakeholders throughout projects, ensuring buy-in and gaining trust along the way. - You are resilient in ambiguous situations and can adapt your role to approach challenges from multiple perspectives. - You don’t shy away from risks or conflicts, instead you take them on and skillfully manage them. - You are eager to coach, mentor and motivate others and you aspire to influence teammates to take positive action and accountability for their work. - You enjoy influencing others and always advocate for technical excellence while being open to change when needed. - You are a proven leader with a track record of encouraging teammates in their professional development and relationships. - Cultivating strong partnerships comes naturally to you; You understand the importance of relationship building and how it can bring new opportunities to our business. Other things to know Learning & Development There is no one-size-fits-all career path at Thoughtworks: however you want to develop your career is entirely up to you. But we also balance autonomy with the strength of our cultivation culture. This means your career is supported by interactive tools, numerous development programs and teammates who want to help you grow. We see value in helping each other be our best and that extends to empowering our employees in their career journeys. Responsible Use of AI in Recruitment At Thoughtworks, we use AI tools to support our recruitment team with administrative tasks such as drafting communications, scheduling interviews and writing job descriptions. Crucially, our AI tools do not screen, assess, rank or make hiring decisions. Every application is reviewed by our team and all selection decisions are made exclusively by our interviewers and hiring managers. We are committed to fairness and responsible AI. We actively manage our AI systems by testing, monitoring for biased outcomes and implementing mitigation measures. We hold our third-party vendors to these same high standards through a rigorous governance process. For additional information, please see our full Thoughtworks AI Policy for Recruitment. Accommodations Thoughtworks is committed to providing reasonable accommodations to qualified applicants with disabilities or sincerely held religious beliefs, practices, or observances, in accordance with applicable law. If you need a reasonable accommodation to complete any part of the application process, participate in interviews, or otherwise engage in the hiring process, you may request an accommodation by completing this form or speaking with your recruiter. Requests may be made at any stage of the application or interview process. Once a request is received, Thoughtworks will engage in an interactive process with the applicant to determine an appropriate accommodation. Applicants are not required to disclose medical diagnoses or detailed personal information in order to request an accommodation. All accommodation requests will be handled in a timely, confidential, and respectful manner, consistent with applicable legal requirements. Requesting an accommodation will not negatively affect your consideration for employment. Company prohibits retaliation against any applicant for requesting an accommodation or participating in the accommodation process. Accommodations made during the recruitment process are not a guarantee of future or continued accommodations once hired. If you are hired by Thoughtworks, and require an accommodation to perform the essential functions of your role, you may be asked to engage in our reasonable accommodation process. Cancellations As a technology consultancy, the projects we undertake are subject to change based on client needs and agreements. While we strive for consistency, please be aware that project scope or availability may shift, or projects may even be cancelled, during the recruitment and selection process, which is often outside of our direct control. Should the project related to this vacancy be significantly altered or cancelled, all impacted candidates will be promptly and duly informed of the change About 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. For 30+ years, we’ve delivered extraordinary impact together with our clients by helping them solve complex business problems with technology as the differentiator. Bring your brilliant expertise and commitment for continuous learning to Thoughtworks. Together, let’s be extraordinary. #LI-Remote Salary Benefits: https://www.thoughtworks.com/en-ca/careers/benefits Salary $156,000—$251,000 CAD See here our AI policy.

Logistics at full potential. At GXO, we’re constantly looking for talented individuals at all levels who can deliver the caliber of service our company requires. You know that a positive work environment creates happy employees, which boosts productivity and dedication. On our team, you’ll have the support to excel at work and the resources to build a career you can be proud of. We’re out to transform transportation logistics through technology, and our multimillion-dollar commitment to IT underscores its importance to our vision. As a Machine Learning Engineer, you will be responsible for designing, building, and maintaining scalable machine learning systems. You will work closely with data scientists, software engineers, and business stakeholders to deploy models into production, ensure system reliability, and optimize performance across GXO’s operations. Pay, benefits and more. We are eager to attract the best, so we offer competitive compensation and a generous benefits package, including full health insurance (medical, dental and vision), 401(k), life insurance, disability and more. What you’ll do on a typical day: - Design, develop, deploy, and maintain ML systems, microservices, and software components that enhance and support supply chain operations and technology. - Ensure software engineering, DevOps, and cybersecurity best practices in development and deployment, including CI/CD pipelines, source control, and secure coding standards. - Design and build, and/or collaborate with data engineering teams to develop data models, pipelines, and integration layers that support and feed ML solutions, ensuring scalability, reliability, and data quality. - Develop ML integration APIs and services using Python, SQL, and frameworks such as Flask and FastAPI with a focus on reliability, latency, and maintainability. - Build agile and portable ML solutions using containerization tools like Docker and Kubernetes. - Implement monitoring, alerting, and observability for ML services. - Collaborate with business and product stakeholders to understand use cases and educate teams on ML capabilities. - Work closely with IT teams (infrastructure, InfoSec, data engineering) to define internal requirements and ensure seamless integration. - Communicate effectively with leadership to secure resources, address issues, and provide project updates. - Take ownership of projects end-to-end with minimal supervision. - Mentor junior engineers on best practices in ML and software development through pair programming, code reviews, and architectural guidance. - Stay current on emerging ML and platform technologies and contribute to the organization’s ML roadmap. - Maintain high-quality technical documentation across systems, services, pipelines, and deployment workflows. What you need to succeed at GXO: At a minimum, you’ll need: - Bachelor’s degree in Computer Science, Statistics, Mathematics, Data Science, Economics, Physics or another analytics-related field, or equivalent related work or military experience - 3–5 years of experience in software engineering, ML engineering, or data science, with at least 2 years focused on designing, building, and deploying scalable, production-grade machine learning systems. - Strong proficiency in cloud environments (GCP preferred; AWS and Azure acceptable). - Expertise in Python, APIs, SQL, system design, DevOps/MLOps, and familiarity with distributed systems. - Familiarity with common ML frameworks such as TensorFlow, scikit-learn, PyTorch, and related tooling. - Experience in monitoring, troubleshooting, and optimizing deployed solutions. - Strong analytical and problem-solving skills. - Strong understanding of all stages of the ML lifecycle. It’d be great if you also had: - Familiarity with logistics systems and supply chain systems (e.g., WMS, OMS, TMS). - Experience with Snowflake and its ecosystem. - Hands-on experience with GCP Vertex AI. - Experience with JavaScript and integrating ML outputs in user-facing applications. We engineer faster, smarter, leaner supply chains. GXO is a leading provider of cutting-edge supply chain solutions to the most successful companies in the world. We help our customers manage their goods most efficiently using our technology and services. Our greatest strength is our global team – energetic, innovative people of all experience levels and talents who make GXO a great place to work. We are proud to be an Equal Opportunity/Affirmative Action employer. Qualified applicants will receive consideration for employment without regard to race, sex, disability, veteran or other protected status. GXO adheres to CDC, OSHA and state and local requirements regarding COVID safety. All employees and visitors are expected to comply with GXO policies which are in place to safeguard our employees and customers. All applicants who receive a conditional offer of employment may be required to take and pass a pre-employment drug test. The above statements are intended to describe the general nature and level of work being performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all responsibilities, duties and skills required of personnel so classified. All employees may be required to perform duties outside of their normal responsibilities from time to time, as needed. Review GXO's candidate privacy statement here.

• Architect the ML Ecosystem: You will own the end-to-end lifecycle of our ML infrastructure, designing a scalable, modern environment that enables models to thrive in production. • Productionize Innovation: Partner closely with our Data Science team to take complex algorithms from the "lab" to the "real-world", building the high-performance pipelines required to scale them. • Engineer Feature Intelligence: Design and maintain both offline and online feature stores, ensuring our models have the high-quality data they need for instant decision-making. • Escale the Data Platform: Collaborate with Data Engineers to evolve our data lake and ETL architectures, ensuring our data platform remains robust and future-proof. • Ensure System Health: Lead the monitoring and observability strategy for all production models, ensuring reliability and performance through proactive maintenance. • Shape Technical Strategy: Act as a key stakeholder in architectural decisions, helping the broader team define the strategy for our data products and event-driven architectures.