Machine Learning Engineer

Thomson Reuters; McLean (VA); On-site; USD 102,000 - 190,000; Full time

Benefits offered by this job

Tuition reimbursement

401(k)

Paid time off

Paid holidays

Life insurance

Parental leave

Job summary

Thomson Reuters seeks a Machine Learning Engineer to develop, deploy, and optimize ML systems powering an investigative platform used by thousands of external users. You will build models across text, image, embeddings, and structured data, focusing on classification, search, similarity, and entity resolution in large-scale data pipelines.

You will collaborate with DevOps, software, data engineering, product, and client stakeholders to ensure robust, interpretable, and responsible AI solutions

Qualifications

• 3+ years of hands-on experience developing, deploying, scaling, and monitoring machine learning models or data science solutions in production environments.
• Bachelor's degree in Statistics, Computer Science, Mathematics, or related technical discipline.
• Strong foundation in machine learning, statistics, experimentation, and applied data science.
• Experience with production pipelines and large-scale data where latency and compute matter.
• Experience with multimodal data (text, image, embeddings, structured data).
• Strong command of Python and data science libraries.
• Hands-on experience with Bash, SQL, and Docker.
• Experience designing experiments and evaluating models in production.
• Ability to trade off model quality, latency, and cost in production.
• Strong communication with technical and non-technical stakeholders.

Responsibilities

• Develop, evaluate, deploy, and improve machine learning models and workflows in high-volume production pipelines.
• Build and enhance ML solutions for classification, ranking, similarity scoring, search, retrieval, and entity resolution across multimodal data.
• Work with text, image, embedding-based features to improve downstream ML systems.
• Conduct experiments, threshold tuning, and error analysis to improve precision and recall.
• Collaborate with engineering and research teams to design, deploy, monitor, and maintain scalable ML systems.
• Guide data pipeline architecture from a data science perspective with robustness and reproducibility in mind.
• Monitor model and pipeline performance and adjust retraining strategies as needed.
• Defining how models and retrieval systems should be developed and operationalized in collaboration with teams.
• Consider ethical and practical implications of ML in sensitive contexts.

Skills

Python

AWS

Bash

SQL

Docker

Multimodal data

Production pipelines

Experimentation

Model deployment

Communication

Education

Bachelor's degree in a quantitative field

Tools

Docker

AWS

Job description

life insurance, parental leave, paid time off, paid holidays, tuition reimbursement, 401(k)

We are seeking a Machine Learning Engineer to develop, operationalize, and improve machine learning systems that power a mission-driven investigative platform used by thousands of external users . The platform turns large volumes of data into actionable intelligence that helps law enforcement identify and respond to cases of child exploitation more quickly . This role sits at the intersection of applied machine learning, data science, and production systems, with a focus on building and deploying solutions that leverage machine learning, computer vision, natural language processing (NLP), embeddings, large language models (LLMs), multimodal large language models (MLLMs), and statistical methods to power mode ling and retrieval workflows that operate reliably on large-scale, multimodal data.

About the Role

As a Machine Learning Engineer, you will be responsible for selecting, developing, fine-tuning, evaluating, deploying and optimizing machine learning solutions for scalable production environments. This includes building and refining models and workflows for classification, search and retrieval, similarity scoring, record linkage, and entity resolution across text, image, embedding s , and other structured and unstructured data types .

You will need to make sound trade-offs across model quality, latency, throughput, interpretability, cost, and maintainability . You will collaborate closely with a cross-functional team of DevOps engineers, S oftware D evelopers, D ata E ngineers, P roduct M anagers, and c lient stakeholders to enhance the platform's capabilities for its investigator user base.

This role is ideal for a mission-driven individual who thrives in a dynamic and ambiguous environment, enjoys solving complex applied machine learning problems, communicates clearly with both technical and non-technical stakeholders, and is passionate about building reliable, responsible AI solutions that support sensitive real-world investigative workflows.

Key Responsibilities

• Develop, evaluate, deploy, and improve machine learning models and workflows in high volume production pipelines .
• Build and enhance applied ML solutions for a range of tasks, including classification, ranking, similarity scoring, search, retrieval and entity resolution across large-scale multimodal data .
• Work with text, image, embedding-based, and structured or semi-structured features to improve downstream ML systems .
• Conduct experimentation, threshold tuning, and error analysis to improve precision, recall, and overall system performance .
• Collaborate with engineering and research teams to design, build, deploy, monitor, and maintain scalable , production ML system s .
• Help define how models and retrieval systems should be developed, evaluated, operationalized, and monitored over time .
• Monitor model and pipeline performance, identify degradation or drift, and improve retraining strategies, feature logic, and workflow behavior as needed .
• Guide data pipeline architecture from a data science perspective, with a focus on robustness, scalability, reproducibility, and alignment with AWS and broader data engineering practices .
• Research and experiment with state-of-the-art AI/ML methodologies and identify practical opportunities to apply them within the platform .
• Ensure ML solutions are developed and applied responsibly, with careful attention to ethical and practical considerations in sensitive investigative contexts .
• Identify and integrate additional data sources to enhance investigative capabilities .
• Contribute directly to product development by working closely with product and client stakeholders to refine requirements, communicate findings, and deploy solutions .
• Provide thought leadership on emerging data science trends and opportunities for growth .
• Participate in a rotating on-call schedule to address critical emergencies and help ensure system availability .

About You

• 3+ years of hands-on experience developing, deploying, scaling, and monitoring machine learning models or data science solutions in production environments .
• Bachelor's degree in a quantitative field such as Statistics, Computer Science, Mathematics, Physical/Biological Sciences, or related technical discipline .
• Strong foundation in machine learning, statistics, experimentation, and applied data science .
• Experience working with production pipelines and large-scale data where modeling decisions must account for scalability, latency, throughput, and compute constraints .
• Experience working with multimodal data, including combinations of text, image, embeddings, and structured or un structured signals .
• Strong command of Python and common data science and machine learning libraries .
• Hands-on experience with AWS or similar cloud environments, production data/ML pipelines, and collaboration with data engineering and platform teams .
• Hands-on experience with Bash, SQL, and Docker .
• Experience designing experiments, evaluating models rigorously, and using error analysis to drive iterative improvements .
• Demonstrated ability to make informed trade-offs regarding model selection, implementation, evaluation, and deployment in production systems .
• Ability to recommend how models and ML workflows should be developed and operationalized in collaboration with engineering and product teams .
• Strong understanding of the ethical and practical considerations involved in applying ML methods in sensitive contexts .
• Comfort working in an ambiguous environment with shifting priorities .
• Ability to communicate clearly with both technical and non-technical stakeholders .
• Strong planning, organizational, and time management skills .
• Team-oriented mindset with the ability to work independently, take initiative, and collaborate cross-functionally .
• Ability to obtain and maintain a U.S. national security clearance .
• U.S. citizenship is essential to comply with government contract, agency, or federal government requirements .

#LI-SW1

What's in it For You?

• Flexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work-life balance.
• Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow's challenges and deliver real-world solutions. Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI-enabled future.
• Industry Competitive Benefits: We offer comprehensive benefit plans to include flexible vacation, two company-wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing.
• Culture: Globally recognized, award-winning reputation for inclusion and belonging, flexibility, work-life balance, and more. We live by our values: Obsess over our Customers, Compete to Win, Challenge (Y)our Thinking, Act Fast / Learn Fast, and Stronger Together.
• Social Impact: Make an impact in your community with our Social Impact Institute. We offer employees two paid volunteer days off annually and opportunities to get involved with pro-bono consulting projects and Environmental, Social, and Governance (ESG) initiatives.
• Making a Real-World Impact: We are one of the few companies globally that helps its customers pursue justice, truth, and transparency. Together, with the professionals and institutions we serve, we help uphold the rule of law, turn the wheels of commerce, catch bad actors, report the facts, and provide trusted, unbiased information to people all over the world.

In the United States, Thomson Reuters offers a comprehensive benefits package to our employees. Our benefit package includes market competitive health, dental, vision, disability, and life insurance programs, as well as a competitive 401k plan with company match. In addition, Thomson Reuters offers market leading work life benefits with competitive vacation, sick and safe paid time off, paid holidays (including two company mental health days off), parental leave, sabbatical leave. These benefits meet or exceeds the requirements of paid time off in accordance with any applicable state or municipal laws. Finally, Thomson Reuters offers the following additional benefits: optional hospital, accident and sickness insurance paid 100% by the employee; optional life and AD&D insurance paid 100% by the employee; Flexible Spending and Health Savings Accounts; fitness reimbursement; access to Employee Assistance Program; Group Legal Identity Theft Protection benefit paid 100% by employee; access to 529 Plan; commuter benefits; Adoption & Surrogacy Assistance; Tuition Reimbursement; and access to Employee Stock Purchase Plan.Thomson Reuters complies with local laws that require upfront disclosure of the expected pay range for a position. The base compensation range varies across locations. For any eligible US locations, unless otherwise noted, the base compensation range for this role is $102,200 USD - $189,800 USD. Base pay is positioned within the range based on several factors including an individual's knowledge, skills and experience with consideration given to internal equity. Base pay is one part of a comprehensive Total Reward program which also includes flexible and supportive benefits and other wellbeing programs. This role may also be eligible for an Annual Bonus based on a combination of enterprise and individual performance.This job posting will close 10/05/2026.

About Us

Thomson Reuters informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. We serve professionals across legal, tax, accounting, compliance, government, and media. Our products combine highly specialized software and insights to empower professionals with the data, intelligence, and solutions needed to make informed decisions, and to help institutions in their pursuit of justice, truth, and transparency. Reuters, part of Thomson Reuters, is a world leading provider of trusted journalism and news.

We are powered by the talents of 26,000 employees across more than 70 countries, where everyone has a chance to contribute and grow professionally in flexible work environments. At a time when objectivity, accuracy, fairness, and transparency are under attack, we consider it our duty to pursue them. Sound exciting? Join us and help shape the industries that move society forward.

As a global business, we rely on the unique backgrounds, perspectives, and experiences of all employees to deliver on our business goals. To ensure we can do that, we seek talented, qualified employees in all our operations around the world regardless of race, color, sex/gender, including pregnancy, gender identity and expression, national origin, religion, sexual orientation, disability, age, marital status, citizen status, veteran status, or any other protected classification under applicable law. Thomson Reuters is proud to be an Equal Employment Opportunity Employer providing a drug-free workplace.

We also make reasonable accommodations for qualified individuals with disabilities and for sincerely held religious beliefs in accordance with applicable law. More information on requesting an accommodation here.

More information about Thomson Reuters can be found on thomsonreuters.com