Job Description
The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A leading global technology organization is developing advanced data and evaluation infrastructure that supports the next generation of artificial intelligence. Its AI-focused team combines machine learning with a large-scale global human network to produce high-quality, model-ready data for advanced AI systems.
The team operates with a startup-style approach while benefiting from extensive global infrastructure and resources. Its work spans multiple AI modalities, including text, images, video, audio, physical AI, and autonomous vehicle technologies, with operations extending across numerous countries.
The organization is seeking a Sr Staff Machine Learning Engineer – Uber AI Solutions to take ownership of significant technical and business initiatives. The role combines machine learning, backend distributed systems, product development, customer engagement, and business growth.
The successful candidate will be expected to own a complete product or business vertical, from defining its direction and identifying growth opportunities to building the underlying technology and delivering measurable business outcomes. This position is suited to an experienced technical leader who thrives in ambiguous environments and wants substantial ownership over both engineering and business results.
Key Responsibilities
- Build machine learning and backend systems that enable sustainable business growth while directly addressing complex technical challenges.
- Own a complete product or business vertical from strategy and development through execution and measurable results.
- Establish direction, identify high-value growth opportunities, and drive business metrics such as revenue, customer adoption, and market reach.
- Make strategic and technical decisions in ambiguous and rapidly changing environments.
- Serve as a trusted technical partner for important customer relationships and use customer insights to influence product development.
- Collaborate closely with product managers and engineering teams to deliver scalable AI-powered products.
- Identify high-leverage opportunities and translate them into measurable business impact.
- Build and develop engineering teams while establishing high technical and organizational standards.
- Balance technical execution with product strategy and commercial objectives.
- Drive initiatives from early concepts through production-scale implementation.
Required Qualifications
- Master’s or PhD in Computer Science, Machine Learning, Electrical Engineering, Mathematics, or a related discipline.
- 7+ years of experience building and shipping machine learning-powered products.
- Demonstrated experience owning both technology and business outcomes for a significant product area.
- Proven track record of driving measurable business growth, including revenue, adoption, or market expansion.
- Deep expertise in machine learning systems and backend distributed systems.
- Experience building and operating production systems that can scale alongside business growth.
- Demonstrated ability to identify high-impact opportunities in ambiguous environments and convert them into meaningful business results.
- Exceptional communication and leadership skills.
- Ability to align customers, product teams, engineers, and business leaders around strategic growth objectives.
Preferred Qualifications
- Experience taking a product or business line from an early-stage concept to meaningful scale.
- Experience working in a startup or startup-like environment with ownership of revenue and growth.
- Experience leading an applied AI product domain such as real-world data, agentic environments, AI evaluation, multimodal machine learning, or multilingual machine learning.
- Expertise in Generative AI and large language model systems at production scale, including architecture, evaluation, safety, and responsible deployment.
- Deep knowledge of physical-world data and physical AI.
- Experience with agentic reinforcement learning environments and evaluation.
- Experience working with multilingual and audio AI systems.
- Experience with robotics and egocentric data.
- Demonstrated ability to manage and develop strategic customer relationships.
- Strong record of delivering significant business outcomes through AI and machine learning technologies.
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