Senior Machine Learning Engineer
Summary
Designs, builds, and deploys production-grade AI/ML models (NLP, computer vision) to tackle online safety challenges, collaborating with cross-functional teams to create scalable solutions with measurable impact.
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Machine Learning Engineer based in United States.
This role offers the opportunity to apply advanced machine learning expertise to solve complex challenges with meaningful social impact.
The Senior Machine Learning Engineer will design, develop, and deploy production-grade models that support critical online safety initiatives.
Working within a collaborative and mission-driven environment, this position combines cutting-edge technology, research, and engineering excellence.
You will partner with engineers, product leaders, designers, and external stakeholders to create scalable AI solutions.
The ideal candidate is passionate about machine learning, thrives in ambiguous problem spaces, and enjoys building systems that make a measurable difference.
This remote-first opportunity allows you to contribute to innovative technology projects while working alongside talented professionals committed to protecting vulnerable communities.
Accountabilities:
The Senior Machine Learning Engineer will lead the development and deployment of advanced machine learning solutions while collaborating across technical and product teams. This role requires strong engineering judgment, creativity, and the ability to transform complex problems into scalable systems.
- Own the complete machine learning lifecycle, including model design, development, testing, evaluation, deployment, and ongoing maintenance.
- Build and improve machine learning systems, classifiers, algorithms, and automated solutions to address complex online safety challenges.
- Identify data sourcing, labeling, and evaluation requirements while partnering with technical program teams to prioritize data initiatives.
- Collaborate with domain specialists to create effective data labeling strategies and improve model performance.
- Design and maintain production-ready ML pipelines, model serving infrastructure, and scalable engineering solutions.
- Partner with software engineers to integrate and maintain models, algorithms, and AI capabilities within products.
- Conduct data analysis, feature engineering, and experimentation to improve technical outcomes and product understanding.
- Clearly communicate technical concepts, model performance, design decisions, and evaluation results to both technical and non-technical stakeholders.
- Collaborate with product managers, designers, and engineering teams to define requirements and deliver impactful solutions.
- Build relationships with external partners and represent technical work through presentations, conferences, and industry forums.
- Stay current with emerging machine learning technologies and identify opportunities to apply new approaches to real-world challenges.
- 5+ years of experience in machine learning, artificial intelligence, or related technical fields.
- Master’s degree, Ph.D., or equivalent professional experience in a quantitative discipline such as computer science, mathematics, statistics, or engineering.
- Proven experience designing, developing, and deploying machine learning systems and production pipelines.
- Experience applying computer vision and/or natural language processing technologies in production environments.
- Strong programming skills in Python and experience with modern ML frameworks and tools.
- Experience with technologies such as PyTorch, TensorFlow/Keras, scikit-learn, Pandas, OpenCV, Hugging Face Transformers, or similar ML libraries.
- Familiarity with cloud infrastructure and engineering tools such as AWS, Kubernetes, Terraform, and CI/CD pipelines.
- Experience working with model optimization, deployment workflows, and scalable ML infrastructure.
- Ability to work effectively in ambiguous environments with evolving requirements.
- Strong collaboration skills with engineers, product teams, designers, and external stakeholders.
- Excellent written and verbal communication skills, especially within distributed teams.
- Passion for machine learning and commitment to creating technology with positive real-world impact.
- Competitive annual compensation range of $154,000 - $212,750, depending on experience, skills, location, and qualifications.
- Remote-first work model with flexibility to work primarily from home.
- Opportunities for professional growth while working on meaningful, mission-driven technology projects.
- Collaboration with talented professionals across engineering, data, product, and research disciplines.
- Company gatherings, team events, and opportunities for in-person collaboration when needed.
- Comprehensive employee benefits package.
- Inclusive and supportive workplace culture that values diverse perspectives and experiences.
- Opportunity to contribute to technology initiatives focused on improving online safety and protecting vulnerable communities.
Requirements:
The ideal candidate is an experienced machine learning professional with a strong background in building and deploying AI systems in production environments. Success in this role requires technical depth, adaptability, strong communication skills, and a commitment to solving complex problems through responsible technology.