This high-impact role will drive the technical direction and oversight for Deep Research Agent Development, translating cutting-edge research in Generative AI, Large Language Models (LLMs), and Agentic Frameworks into robust, scalable, and high-impact production systems that enhance enterprise operations, analytics, and core efficiency.

The ideal candidate thrives in a fast-paced environment, has a passion for both deep technical work and mentoring, and is capable of setting a long-term technical strategy for a critical domain while maintaining a strong, hands-on delivery focus.

Responsibilities

Technical Leadership & Vision

• Set the Technical Roadmap: Define and own the technical strategy, architecture, and roadmap for Deep Research Agents for the Enterprise, ensuring alignment with Scale AI’s overall AI strategy and business goals.

• Drive Breakthrough Research to Production: Lead the end-to-end development, from initial research to production deployment, to landing on customer impact, with a focus on integrating diverse data modalities.

• Core Agent Capabilities Development:

Advanced Knowledge Retrieval: Architect and implement state-of-the-art retrieval systems to ensure the agents provide accurate and comprehensive answers from public and proprietary data sources from enterprises.

Data Analysis: Design and champion the development of data analysis agents that accurately translate complex natural language queries into executable SQL/code against diverse enterprise data schemas.

Multimodal Intelligence: Lead the integration of Multimodal AI capabilities to process and extract structured information from visual documents, tables, and forms, enriching the agent's knowledge base.

Architecture & Design: Design and champion highly scalable, reliable, and low-latency infrastructure and frameworks for building, orchestrating, and evaluating multi-agent systems at enterprise scale.

Technical Excellence: Serve as the technical authority for the team, leading design reviews, defining ML engineering best practices, and ensuring code quality, security, and operational excellence for all agent systems.

Team Leadership & Mentorship

• Lead and Mentor: Technically lead and mentor a team of Machine Learning Engineers and Research Scientists, fostering a culture of innovation, rigorous engineering, rapid iteration, and technical depth.

• Recruiting & Growth: Partner with management to hire, onboard, and grow top-tier talent, helping to shape the long-term structure and capabilities of the team.

• Cross-Functional Influence: Collaborate effectively with Product Managers, Data Scientists, and other engineering/science teams to translate ambiguous, high-level business problems into concrete, executable technical specifications and impactful agent solutions.

Basic Qualifications

• Bachelor's degree in Computer Science, Electrical Engineering, a related field, or equivalent practical experience.

• 8+ years of experience in software development, with at least 6 years focused on Machine Learning, Deep Learning, or Applied Research in a production environment.

• 2+ years of experience in a formal or informal Technical Leadership role (Team Lead, Tech Lead) with a focus on setting technical direction for a domain.

• Deep expertise in Generative AI and Large Language Models (LLMs).

• Demonstrated experience designing, building, and deploying AI Agents or complex Agentic systems in production at scale.

• Experience with large-scale distributed systems and real-time data processing.

Preferred Qualifications

• Advanced degree (Master's or Ph.D.) in Computer Science, Machine Learning, or a related quantitative field.

• Demonstrated experience designing and deploying production-grade Text-to-SQL systems, including handling complex schema linking and query optimization.

• Practical experience with Multimodal AI, specifically integrating OCR and vision-language models for document intelligence and structured data extraction from images/forms.

• Proven experience in one or more relevant deep research areas: Reinforcement Learning (RL), Reasoning and Planning, Agentic Systems.

• Experience with vector databases and advanced retrieval techniques.

• A track record of publishing research papers in top-tier ML/AI conferences (e.g., NeurIPS, ICML, ICLR, KDD).

• Excellent written and verbal communication skills, with the ability to articulate complex technical vision to executive stakeholders and technical peers.

• Experience driving cross-team technical initiatives that have delivered significant business impact.

Compensation

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity-based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

About Us

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

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The ideal candidate will have expertise in multimodality and experience running large-scale experiments. They will be comfortable contributing to complex engineering systems and have a strong grasp of probability, statistics, and machine learning fundamentals.

This is an evergreen role, meaning that the position is open on an ongoing basis. The company receives many applications, and there may not always be an immediate role that aligns perfectly with the candidate's experience and skills. However, they encourage candidates to apply and continuously review applications.

Responsibilities:

• Own research projects on training and performance analysis of multimodal AI models.
• Curate and build large-scale datasets and evaluation benchmarks to advance vision capabilities.
• Work with data infrastructure engineers, pretraining researchers and engineers, and product teams to create frontier multimodal models and the products that leverage them.
• Publish and present research that moves the entire community forward.

Skills and Qualifications:

• Ability to design, run, and analyze experiments thoughtfully, with demonstrated research judgment and empirical rigor.
• Understanding of machine learning fundamentals, large-scale training, and distributed compute environments.
• Proficiency in Python and familiarity with at least one deep learning framework (e.g., PyTorch, TensorFlow, or JAX).
• Comfortable with debugging distributed training and writing code that scales.
• Bachelor's degree or equivalent experience in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding.

Preferred qualifications include research or engineering contributions in visual reasoning, spatial understanding, or multimodal architecture design, experience developing evaluation frameworks for multimodal tasks, publications or open-source contributions in vision-language modeling, video understanding, or multimodal AI, and a strong grasp of probability, statistics, and ML fundamentals.

Logistics:

• Location: San Francisco, California.
• Compensation: $350,000 - $475,000 USD per year, depending on background, skills, and experience.
• Visa sponsorship: Yes.
• Benefits: Generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

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This role requires a passion for understanding and modeling the interactions between AI and society, a strong awareness of the AI alignment and safety landscape, and a penchant for developing novel ideas, methods, interfaces, and tools.

As a Research Scientist at Google DeepMind, you will join a team working to supercharge exploration, assessment, and steering of evolving AI behaviours, with a focus on subjective and creative tasks. You will tackle the underlying research questions to improve collaborative specification of alignment objectives and assessment of adherence to desired behaviours.

Key responsibilities include generating new ideas, executing cutting-edge ideas, communicating research findings, collaborating with other researchers, and driving technical projects.

To be successful in this role, you will need a PhD degree in Computer Science, Machine Learning, or a related technical field, a strong publication record in top machine learning conferences, and demonstrated hands-on experience in developing multimodal AI models and systems.

In addition, experience with large-scale vision language models, fine-tuning and post-training LLMs using RL, and developing agentic AI solutions to complex problems would be an advantage.

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We are looking for an engineering leader who is hands-on with deep learning—comfortable reading/modeling code, not just running it. You will lead, encourage, and develop world-class engineering and data teams distributed across Europe, Asia and the United States.

Key Responsibilities:

• Architect and operationalize NVIDIA’s end-to-end data Inference Acceleration strategy, powering Inferencing and continuous performance improvements.
• Drive Strategic Implementations of TensorRT, VLLM and other accelerated frameworks for inference solutions for Edge and Enterprise devices: Lead Accelerated Computing efforts and solutions for key Metropolis verticals. Set up Proofs of Readiness (PORs) and guide their implementations.
• Leading customer solutions: Collaborate with major Metropolis OEMs and Partners to architect highly accelerated and optimized custom deep learning models and inference pipelines for their specific requirements. Offer direct customer support, including debugging, technical education, and handling customer inquiries for our Metropolis partner and customers. Responsible for drafting and finalizing SOWs with internal customers and partners.
• Performance Benchmarking: Orchestrate efforts to achieve leading performance results on industry benchmarks like MLPerf on various edge and Enterprise devices.
• Technical Leadership & Influence: Function as a technical leader for deep learning across multiple teams, giving oversight and build support. Apply customer insights to influence the composition and structure of upcoming SOC / GPU deep learning hardware.
• Scaling the team: Strategically hiring to meet new demands while also mentoring and adjusting existing teams to new deep learning challenges.
• Representing Nvidia Deep learning solutions in webinars, conferences and partner events

Requirements:

• Masters in Computer Science/Electrical Engineering or equivalent experience.
• A minimum of 8 years of meaningful involvement in machine learning/deep learning research or practical experience, coupled with 7+ years of leadership background and overall 15+ years of industry experience.
• Over 10 years of validated expertise in the embedded software sector, holding technical leadership positions accountable for delivering outstanding production software within a multifaceted setting.
• Deep Knowledge of GPU, CPU and dedicated deep learning architecture fundamentals and low-level performance optimizations using heterogeneous computing.
• Hands-on experience with VLMs, LLMs, or multimodal AI systems applied to perception, data triage, or automated labeling.
• Strong expertise in large-scale data processing, systems build, or machine learning pipelines.
• Strong communication, careful planning, and technical leadership capabilities.

Benefits:

• Competitive salary package and benefits
• Eligible for equity

How to Apply:

Applications for this job will be accepted at least until March 13, 2026.

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