Staff Machine Learning Engineer, Applied Research

For our client, we are seeking a Staff Machine Learning Engineer Applied Research to join the team of a leader in the Consumer Technology space. This role will lead work at the intersection of data, AI-enabled capabilities, and scalable technology delivery. You will work across engineering, product, operations, and business stakeholders to translate complex requirements into practical technology solutions. The position offers the opportunity to influence architecture, execution quality, and the technology capabilities that enable long-term growth within a technology-driven environment.Location: Remote - US based candidates only, no visa sponsorship availableCompensation: $189,308 – $389,753 annuallyResponsibilities Contribute to advanced machine learning and LLM research relevant to the company’s challenges, focusing on search and recommendation systems Gather, analyze, and synthesize data to create intelligent, data-driven models Write high-quality, sustainable code Apply machine learning, natural language processing, and graph analysis to address modeling and ranking issues across various domains Independently scope and resolve moderately complex problemsQualifications MS/PhD in Computer Science, ML, NLP, Statistics, Information Sciences, or a related field 6+ years of industry experience Expertise in machine learning or information retrieval Proficiency in at least one systems language (Java, C++, Python) or one ML framework (Tensorflow, Pytorch, MLFlow) Experience with research and analytical problem-solving Ability to collaborate cross-functionally and communicate effectively Comfort in tackling ambiguous problems and adaptability to changing environmentsBenefits Flexible working model - remote work with occasional in-office collaboration In-office collaboration required 1-2 times per quarter Commitment to equity, inclusivity, and inspiration in the workplaceOur client is an equal opportunity employer. We encourage you to apply even if you don’t meet every qualification—your background could be exactly what this team needs.