Jobgether

Compensation

Full Description

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Machine Learning Engineer, Relevance in the United States. The Machine Learning Engineer will play a pivotal role in developing and deploying cutting-edge machine learning solutions to enhance user engagement and product relevance. You will work across the full ML lifecycle, from exploratory data analysis and model prototyping to production deployment and monitoring. This role requires collaboration with cross-functional teams, including product, engineering, design, and trust & safety, to design impactful solutions. You will analyze and prepare training datasets, implement novel ML techniques, and ensure robust, scalable systems in production. A keen analytical mindset, clean coding practices, and a strong understanding of model observability and performance optimization are essential. This position offers an opportunity to influence product decisions through data-driven insights and advance the user experience on a large-scale platform. Accountabilities Conduct exploratory data analyses and develop proof-of-concept machine learning models to identify opportunities and potential impacts. Collaborate with cross-functional teams to design and implement ML solutions aligned with product objectives. Prepare, clean, and label training datasets, leveraging crowdsourcing techniques when necessary. Train, iterate, and deploy machine learning models to production, including writing supporting backend code. Monitor model performance, debug issues, and continuously iterate to improve accuracy, reliability, and efficiency. Document models, processes, and outcomes clearly to ensure knowledge sharing across the team. Bachelor’s degree in Computer Science, Computer Engineering, or a related field, or equivalent experience. Proven experience in end-to-end machine learning: data analysis, model development, production deployment, performance monitoring, and A/B testing. Strong programming skills in Python or other relevant languages with attention to clean, maintainable code. Experience debugging complex systems with a systematic approach. Ability to work collaboratively in a cross-functional team environment. Strong analytical and problem-solving skills with a curiosity-driven mindset for datasets and user behavior. Excellent written and verbal communication skills, including clear documentation practices. Growth mindset and willingness to learn, adapt, and explore novel ML techniques. Experience with hybrid work models and in-office collaboration 2 days per week (for San Francisco or New York-based roles). Competitive salary and equity plans, with transparency based on role level and location. Comprehensive healthcare, including medical, dental, and vision coverage. Flexible time off, company holidays, and recharge days. Parental leave and lifestyle stipends. Learning and development opportunities, including stipends for continuous education. 401(k) plan with company matching. Hybrid work model fostering collaboration and community engagement. Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching. When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly. 🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements. 📊 It compares your profile to the job’s core requirements and past success factors to determine your match score. 🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role. 🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed. The process is transparent, skills-based, and free of bias, focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team. Thank you for your interest! #LI-CL1