Staff Machine Learning Engineer, AI Researcher

Job Description

• This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Staff Machine Learning Engineer, AI Researcher in the United States. This role offers the opportunity to lead cutting-edge AI and machine learning initiatives, working closely with a highly-skilled team of engineers and researchers. You will design, train, and optimize ML models, translating advanced research into scalable, production-ready systems that solve real-world problems. The position involves building robust ML pipelines, running iterative experiments, and collaborating cross-functionally to integrate AI technologies into key products. This is a remote-friendly, high-impact role where innovation, experimentation, and technical rigor are highly valued. You will have the chance to influence AI strategy, contribute to state-of-the-art research, and deliver solutions that directly benefit customers.
• Accountabilities: Design, develop, train, and evaluate machine learning models across research and applied AI initiatives. Build and maintain robust ML pipelines for data ingestion, feature engineering, model training, and evaluation. Run iterative experiments, test hypotheses, and refine models to improve performance and accuracy. Collaborate with researchers, engineers, and stakeholders to translate academic advances into production-ready solutions. Optimize model performance through fine-tuning, hyperparameter search, and architecture experimentation. Document experimental results, track findings, and share learnings with the broader team. Stay current with AI/ML research trends and identify opportunities to apply new techniques to product solutions. Participate in stand-by, on-call, or off-hours duties during critical research or deployment milestones as needed. Requirements: Bachelor’s degree in Computer Science, Mathematics, Statistics, or a related field (Master’s or PhD preferred). 5+ years of experience in industry or research, with deep hands-on expertise training and evaluating ML models, including language models. Proficiency in Python and ML frameworks such as PyTorch or TensorFlow. Experience with MLOps tooling and infrastructure (e.g., MLflow, Weights & Biases, Kubeflow, or similar). Solid understanding of modern NLP, computer vision, and/or reinforcement learning techniques. Strong analytical and problem-solving skills with the ability to iterate quickly without sacrificing rigor. Excellent communication skills, capable of presenting experimental results to technical and non-technical stakeholders. Ability to work independently and collaboratively in a fast-paced, remote-first environment. Benefits: Competitive salary range: $230,000–$275,000, dependent on experience and location. Comprehensive health, dental, and vision insurance. Short-term disability and life insurance coverage. Paid holidays and generous paid time off. 401(k) plan and company equity. Fertility treatment benefits. Eligibility for a discretionary company-wide bonus. Remote-first work environment with flexible work arrangements.
• Why Apply Through Jobgether? 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
• We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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