Senior Machine Learning Engineer

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. 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. 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. Benefits: 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.

How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
 Why Apply Through Jobgether? 
 
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
 
 
#LI-CL1