Senior Machine Learning Engineer - Refer

Thoughtworks Inc.

Job Overview

Location

Brazil, Brazil

Job Type

Full-time

Full Job Description

📋 Description

• As a Senior Machine Learning Engineer at Thoughtworks, you will be at the forefront of building, maintaining, and testing the sophisticated architecture and infrastructure that powers cutting-edge machine learning applications. You will play a pivotal role in supporting and actively contributing to the design of end-to-end applications and products, ensuring they are robust, scalable, and performant.
• You will be responsible for developing core capabilities within machine learning systems and applications. This includes architecting and implementing ML pipelines, managing model training and deployment processes, and establishing comprehensive monitoring and evaluation frameworks to ensure the continuous health and effectiveness of our ML solutions.
• Your role will involve being the anchor for functional streams of work, providing deep technical expertise, guiding team discussions, and ensuring the timely and successful delivery of assigned tasks and projects. This requires a proactive approach to problem-solving and a commitment to excellence.
• You will collaborate closely with talented data scientists and engineers, translating complex business needs into practical, efficient, and effective machine learning systems and applications. This cross-functional collaboration is key to delivering impactful solutions.
• A significant aspect of your role will be to stay ahead of the curve in the rapidly evolving field of Machine Learning. You will actively explore, evaluate, and implement the latest tools, frameworks, and offerings in the ML landscape, ensuring Thoughtworks remains at the cutting edge of technological innovation.
• You will foster a collaborative problem-solving environment within your team. This involves active listening, clear and effective communication, and providing mentorship to other engineers, helping them to grow their skills and contribute more effectively.
• You will contribute significantly to the development and execution of the team's overall ML strategy. This means aligning technical capabilities with overarching business objectives, ensuring that our ML initiatives drive tangible value and support the company's strategic goals.
• Proactively identifying and addressing challenges related to ML systems and applications will be a core responsibility. You will be expected to propose innovative solutions, implement improvements, and drive continuous optimization of our ML infrastructure and applications.
• You will contribute to the design and drive the development of robust, scalable architectures and infrastructure for deploying and managing machine learning (ML) applications. This includes ensuring high availability, optimal performance, and stringent security measures are in place.
• You will own the development and maintenance of core functionalities within ML applications. This encompasses the entire lifecycle, from initial development through to ongoing maintenance and enhancement.
• You will drive the functional stream of work by providing unparalleled technical expertise, expertly handling team discussions, and ensuring the timely delivery of all assigned tasks, acting as a key driver of project success.
• You will facilitate collaborative problem-solving within the team by actively listening, communicating effectively, and mentoring other engineers, fostering a culture of shared learning and continuous improvement.
• You will contribute to the development and execution of the team's overall ML strategy, ensuring that technical capabilities are seamlessly aligned with critical business objectives.
• You will proactively identify and address challenges related to ML systems and applications, proposing effective solutions and implementing necessary improvements to maintain system integrity and efficiency.
• You will be instrumental in building, deploying, and maintaining ML systems using relevant ML techniques and platforms such as Scikit-learn, Tensorflow, MLFlow, Kubeflow, and Pytorch.
• You will apply MLOps principles and CI/CD practices to the ML lifecycle, ensuring efficient and reliable deployment and management of models.
• You will leverage your experience in designing and operating the infrastructure required to run diverse ML training and serving workloads, considering factors like on-premise vs. cloud infrastructure, infrastructure as code, and robust monitoring solutions.
• You will utilize your hands-on experience with on-premise and cloud services like Azure, AWS, GCP, or Databricks, along with their associated managed ML services, to build and deploy sophisticated ML pipelines.
• You will demonstrate a strong understanding of stakeholder management, effectively liaising between clients and other key stakeholders throughout projects to ensure buy-in and build trust.
• You will exhibit resilience in ambiguous situations, adapting your role to approach challenges from multiple perspectives and finding innovative solutions.
• You will confidently take on risks and conflicts, managing them skillfully to achieve positive outcomes.
• You will actively coach, mentor, and motivate teammates, aspiring to influence them to take positive action and accountability for their work.
• You will enjoy influencing others and advocating for technical excellence while remaining open to change and new approaches when necessary.

🎯 Requirements

• Proven experience in building, deploying, and maintaining ML systems using relevant ML techniques and platforms (e.g., Scikit-learn, Tensorflow, MLFlow, Kubeflow, Pytorch).
• Hands-on experience with on-premise and cloud services (e.g., Azure, AWS, GCP, Databricks) for building and deploying ML pipelines.
• Proficiency in scripting languages such as Python or Shell for automation and task streamlining.
• Experience with MLOps principles and CI/CD applied to the ML lifecycle.
• Strong understanding of distributed systems and scalable architectures for large-scale ML applications.
• Experience in writing clean, maintainable, and testable code, with a focus on refactoring and readability.
• Familiarity with key ML concepts, algorithms, and frameworks, and a solid understanding of ML model lifecycles.
• Experience designing and operating infrastructure for ML workloads (on-premise/cloud, IaC, monitoring).
• Excellent stakeholder management and communication skills.
• Resilience and adaptability in ambiguous situations.

🏖️ Benefits

• Opportunities for continuous learning and professional development through interactive tools and numerous development programs.
• A supportive cultivation culture with teammates eager to help you grow and achieve your career aspirations.
• Hybrid working model offering flexibility between remote work and Thoughtworks offices.
• Exposure to cutting-edge tools, frameworks, and offerings in the Machine Learning landscape.
• A collaborative environment that encourages problem-solving and knowledge sharing.
• Involvement in diverse and impactful digital innovation projects for global clients.

Skills & Technologies

Python

AWS

Azure

GCP

TensorFlow

Senior

Remote

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About Thoughtworks Inc.

Thoughtworks is a global technology consultancy that integrates strategy, design and engineering to drive digital transformation. Founded in 1993, it partners with organizations to create adaptive platforms, modernize legacy systems, and build data-driven products. The company champions agile and lean practices, open source contributions, and responsible technology. Its 10,000+ employees across 17 countries deliver custom software, cloud and AI solutions for Fortune 500 companies and nonprofits. Thoughtworks also advocates for social justice, diversity in tech, and sustainable software development.

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