Sr. Staff AI/Machine Learning Engineer (Remote - US)

This position is posted by Jobgether on behalf of Flex. We are currently looking for a Sr. Staff AI/Machine Learning Engineer in United States. This role offers the opportunity to lead the development and deployment of advanced AI and machine learning systems that power high-impact fintech products. You will drive the full ML lifecycle, from research and data exploration to production deployment and continuous optimization, ensuring models deliver reliable, scalable, and high-performing solutions. The position emphasizes cross-functional collaboration with data scientists, engineers, and product teams to translate complex business problems into actionable ML solutions. You will have a significant influence on technical strategy, infrastructure design, and the adoption of cutting-edge ML frameworks, all while championing responsible AI practices. The environment is fast-paced, high-growth, and innovation-driven, offering the ability to shape the future of AI-driven financial technology solutions. Accountabilities: Lead the design, development, and deployment of scalable machine learning models for production fintech applications. Collaborate with cross-functional teams to translate complex business challenges into ML solutions that directly impact product and business goals. Build, maintain, and optimize ML systems, including data pipelines, feature stores, model serving infrastructure, and MLOps workflows. Continuously monitor, evaluate, and enhance model performance through experimentation, hyperparameter tuning, and iterative improvements. Implement state-of-the-art AI/ML tools, frameworks, and methodologies to ensure technical excellence and maintain competitive advantage. Champion responsible AI practices focusing on fairness, explainability, bias mitigation, and auditability. Stay current with emerging trends in AI, machine learning, and scalable software deployment to keep systems cutting-edge. Requirements Master’s or Ph.D. in Computer Science, Engineering, Statistics, or a related technical field. 6+ years of machine learning experience, including 3+ years in senior or staff-level roles. Expert proficiency in Python or similar languages, with experience in TensorFlow, PyTorch, and scikit-learn. Extensive experience with cloud platforms (AWS, GCP, Azure) and ML infrastructure tools (SageMaker, Vertex AI, MLflow). Proficient in distributed computing frameworks (Spark, Kubernetes) and data workflow tools (Pandas, Airflow). Proven track record of designing, building, and deploying end-to-end ML systems at scale in production. Strong background in performance optimization, version control, CI/CD, and ML lifecycle management. Excellent analytical, problem-solving, and communication skills for collaboration across teams. Benefits Competitive base salary: NY $221,000–$237,000; other states $209,000–$225,000. 100% company-paid medical, dental, and vision coverage. 401(k) plan and company equity participation. Unlimited paid time off plus 13 company-paid holidays. Parental leave and Flex Cares Program (non-profit match and pet adoption coverage). Free Flex subscription for employees. Work in a diverse, inclusive, and collaborative culture across US and international locations. 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! Originally posted on Himalayas