Applied Ai

Applied Ai Data Jobs

4 jobs found

Today

Lead AI Engineer

Qualified Health PBC Palo Alto, CA

Palo Alto, CA

Today

$230k - $350k/yr Full time Agentic Ai Ai Agent Ai Agent Platform

Apply Now

Job Description

Qualified Health PBC is building agentic AI systems across its full product portfolio, and it’s looking for a Lead AI Engineer to set the technical vision and deliver the platform strategy. Based in Palo Alto, CA (onsite), this role spans multi-year infrastructure planning, org-wide standards for LLM evaluation and safety, and hands-on engineering on the most ambiguous problems. With an emphasis on mentoring, the Lead AI Engineer will also help shape how applied AI roles grow across the organization.

Responsibilities

Define the multi-year technical strategy and architecture for agentic workflow infrastructure supporting the full Qualified Health product portfolio, including 100+ workflows and growth.
Serve as the applied AI engineering voice in cross-functional and leadership-level decisions on product direction, build-vs-buy, and platform investment.
Set org-wide engineering standards for LLM evaluation, deployment, safety, and monitoring, aligning with the company’s broader AI governance approach.
Act as a technical escalation point for the most challenging, high-ambiguity problems across product lines.
Mentor and develop Staff-level engineers, contributing to the technical career ladder for applied AI roles.
Stay ahead of the frontier by evaluating emerging models, frameworks, and techniques (including OpenAI, Anthropic, and Mistral) and determining what to adopt at Qualified Health.
Partner with founders and engineering leadership on how AI infrastructure investment ties to overall company strategy.

Requirements

Python required with a deep software engineering foundation and a track record of architecting systems used company-wide.
8+ years building production software, including 4+ years building and scaling AI-powered / LLM-driven applications in production.
Proven experience setting technical direction and standards adopted across multiple teams, beyond a single product line.
Deep expertise in MLOps, model deployment, and workflow automation at an organizational or platform level.
Ability to operate with full autonomy on ambiguous, high-stakes technical and strategic problems.
Strong history influencing technical decisions at the leadership level, including with non-technical stakeholders.

Technologies

Python
LLM
MLOps
OpenAI
Anthropic
Mistral

Benefits

Competitive salaries with equity packages
Robust medical/dental/vision insurance
Flexible working hours
Hybrid work options
Inclusive environment that fosters creativity and innovation
Eligible for equity and benefits

Desirable Skills

Bachelor’s degree + 10 years OR Master’s degree + 8 years in Computer Science, Engineering, or related field (or equivalent experience).
Recognized expertise in applied AI and agentic systems (internally or externally), such as talks, publications, open source, or prior platform-level roles.
Experience building AI infrastructure in a regulated or high-stakes domain such as healthcare or finance.
History of founding or scaling a technical function from the ground up in a startup environment.
Experience mentoring Staff-level engineers and shaping technical career ladders.

Salary: USD 230,000 - 350,000 per year. Experience: 8+ years.

View full job page →

Today

Mid-Level AI & Machine Learning Engineer

Fieldwire San Francisco, CA

San Francisco, CA

Today

$170k - $195k/yr Full time AI Ai Engineer Ai/ml Developer

Apply Now

Job Description

Fieldwire is building AI foundations that help turn construction documents and images into usable information inside its platform. As a Mid-Level AI & Machine Learning Engineer, you will adapt and deploy AI models for document and image understanding, with a focus on model performance in production and context-aware outputs that fit users’ workflows.

This hybrid role is based in San Francisco, California, with Fieldwire’s headquarters centrally located off Embarcadero BART.

What you will do

Architect, build, and maintain AI foundations across the full stack, embedding capabilities into core platform functionality
Evaluate and select open-source models, then adapt them to domain-specific use cases using fine-tuning, transfer learning, and lightweight training
Deploy and operate models in Fieldwire’s infrastructure, including GPU-backed environments with an emphasis on inference performance, resource utilization, throughput, and latency
Build solutions for image understanding, including visual object detection, classification, and segmentation
Extract and interpret information from PDFs, scanned documents, images, and other complex visual content by combining OCR, document layout analysis, and multimodal models
Apply AI and computer vision techniques to surface relevant, context-aware information within users’ workflows
Debug production issues across services and multiple levels of the stack
Contribute to improving engineering standards, tooling, and processes

Required qualifications

Bachelor’s or Master’s degree in Computer Science (or equivalent work experience)
3+ years of experience in a Fullstack, Backend, AI Engineering, or Machine Learning role
Practical experience in machine learning, including training, evaluating, and deploying models
Hands-on experience with computer vision and image-processing techniques
Knowledge of modern toolchains used to develop high-quality applications
Strong ability to write clean, well-tested, and modular code

Technologies you may work with

Open-source models, fine-tuning, transfer learning
OCR, document layout analysis, multimodal models
Transformers, vision-language models
GPU-backed environments
Rust, Ruby on Rails, Angular

Preferred experience

Working with pretrained models and adapting them to domain-specific tasks through fine-tuning and transfer learning
Understanding modern model architectures, including transformers and vision-language models
Experience with image and document processing, such as OCR, document layout analysis, or extracting structured information from PDFs and images
Experience building production systems, preferably in Rust, Ruby on Rails, or Angular

Compensation

Estimated pay range: $170,000 - $195,000 per year
Actual salary offer will consider factors including skills, qualifications, and experience

Benefits

Corporate bonus with a range up to 30%

View full job page →

1d ago

Legal AI Engineer, Litigation

Debevoise & Plimpton LLP New York, NY

New York, NY

1d ago

$240k - $300k/yr Full time Applied Ai Artificial Intelligence Legal Technology

Apply Now

Job Description

Debevoise & Plimpton LLP seeks a Legal AI Engineer, Litigation to join the Practice Systems & Applied AI team within the Information Services Department. Based in New York, NY (onsite), this role supports litigation teams and client engagements by advising on responsible, practical AI application across litigation workflows and legal service delivery.

Role focus

Work with the Head of Practice Systems & Applied AI to help execute the Firm’s AI strategy and expand responsible AI use across litigation practices and client engagements.
Act as a litigation-focused subject-matter expert, supporting lawyers as they engage clients on the Firm’s AI capabilities, approach, governance, and experience.
Advise litigation clients and matter teams on practical AI application, including use-case development, workflow design, adoption considerations, and responsible-use practices.

Client and attorney enablement

Independently prepare for and lead client-facing presentations, meetings, demonstrations, trainings, and continuing legal education programs on AI concepts, capabilities, risks, and legal use cases.
Serve as a hands-on resource for AI use on specific matters, including guidance on use-case selection, workflow design, prompt development, quality control, and attorney review.
Develop litigation practice-specific AI guidance, demonstrations, use cases, talking points, playbooks, and training materials for lawyers and client teams.
Educate attorneys on accurately and credibly discussing AI capabilities, limitations, risks, governance, and potential value with clients.

Litigation workflow expertise and tool evaluation

Apply litigation legal practice knowledge to evaluate how AI may support drafting, review, discovery, research, case management, investigations, enforcement matters, regulatory proceedings, and other litigation processes.
Translate litigation and client needs into clear business and functional requirements for the Applied AI Engineering & Solutions team and other technical stakeholders.
Support evaluation and rollout of new AI tools by assessing legal-practice relevance, developing adoption strategies, and helping lawyers incorporate approved capabilities into their work.
Contribute to the Applied AI roadmap by identifying litigation practice and client priorities, evaluating potential impact, and recommending initiatives for research, development, or implementation.

Business development and internal guidance

Support pitches, requests for proposals, client alerts, panel discussions, and other business development efforts by contributing AI-related content and presenting the Firm’s approach to legal AI.
Prepare communications, briefings, and recommendations for Firm leadership and other stakeholders regarding AI adoption, litigation client and matter activity, practice opportunities, and emerging legal-industry developments.

Staying current

Stay abreast of advances in AI, legal technology, legal-service delivery, client expectations, professional responsibility, and industry practices to keep guidance current and practical.

Required qualifications

J.D. required; minimum of three years working as a practicing attorney, legal innovation professional, knowledge management attorney, practice support attorney, or similar law firm professional.
Demonstrated knowledge of litigation legal practices, litigation matter workflows, attorney work product, and delivery of legal services in a litigation practice context.
Proven ability to independently lead presentations, meetings, trainings, and substantive discussions with clients, lawyers, and senior stakeholders.
Experience advising lawyers or clients on AI, legal technology, knowledge management, innovation, legal operations, or technology-enabled legal-service delivery.
Strong working knowledge of generative AI, large language models, prompt design, AI-assisted legal workflows, and the opportunities and limitations of AI in legal practice.
Experience developing legal or business requirements and working with technical teams to design, evaluate, or implement technology solutions.
Understanding of confidentiality, privilege, data governance, professional responsibility, privacy, and ethical considerations associated with AI in legal services.
Proven track record of leading complex, cross-functional initiatives from opportunity identification through implementation, adoption, and ongoing support.
Exceptional presentation and public-speaking skills, with credibility in discussions with clients, Partners, Firm leadership, attorneys, and professional staff.
Deep understanding of litigation legal practice areas and the ability to analyze workflows across different litigation matter types, including investigations, discovery, research, and other litigation processes.
Strong communication skills, including executive briefings, client materials, training content, demonstrations, and practice-specific guidance.
Strong judgment, professional credibility, and interpersonal skills to influence senior stakeholders and navigate sensitive considerations.
Strong organizational and project-management skills to manage multiple litigation, client, practice, training, and implementation initiatives in a fast-paced environment.

Technologies

Generative AI
Large language models
Prompt design
AI-assisted legal workflows

Compensation

USD 240,000 - 300,000 per year.

How to apply

A resume is required.
Please include your salary requirements and indicate where you saw the position posted.
Send required materials to Human Resources at jferrigno@debevoise.com or call 212.909.8310.

View full job page →

6d ago

Applied AI Engineer, Startups (Physical AI)

Anthropic San Francisco, CA

San Francisco, CA

6d ago

$280k - $320k/yr Full time Applied Ai Artificial Intelligence Engineer

Apply Now

Job Description

Anthropic is building applied AI capabilities with teams focused on bringing Claude into real-world products. On the Startups (Physical AI) team, you will work as a deep technical advisor to physical-world startups, helping them architect, evaluate, and scale AI-powered systems across both software and hardware workflows.

This hybrid role in San Francisco pairs hands-on engineering support with customer-facing collaboration, from architecture reviews and prototype work to traveling on-site for workshops and implementation guidance.

What you’ll do

Advise high-potential startups building in the physical world, working with teams whether Claude is integrated inside their product or inside the way they design, test, and run their own hardware.
Partner hands-on with startup software and hardware teams using pair programming and architecture reviews, spanning workflows from design and simulation through test, production, and operations.
Develop prototypes and technical documentation, including evaluation suites, benchmarks based on real engineering tasks, AI engineering techniques, and architecture diagrams.
Create reference implementations and sample code that others can adopt, such as integrating Claude with CAD, simulation, design tools, or industrial automation.
Collaborate closely with Applied AI Architects to maintain context and continuity across customer engagements.
Spot recurring challenges in applying AI to physical systems, including reading drawings, 3D geometry, board layout and routing, GD&T, latency and on-premise constraints, and physical safety, then build repeatable evaluations and solutions and share insights with Product, Engineering, Research, and the broader Applied AI team.
Produce technical content for startup audiences, including documentation, tutorials, and sample code.
Engage the startup community through hackathons, webinars, technical office hours, and startup-focused events.
Travel to customer sites for workshops, implementation guidance, and relationship building.

What you bring

Deep engineering experience in a physical discipline such as mechanical, electrical, aerospace, robotics, semiconductor, manufacturing, or civil engineering, gained through designing, building, or operating real hardware, along with strong opinions on bridging what AI can do today with how physical systems get built.
4+ years of technical experience as a software engineer, ML or research engineer, robotics or controls engineer, hardware or systems engineer, or technical founder, with either production experience building LLM-powered applications (prompting, context engineering, agent architectures, evaluation frameworks, and deployment at scale) or a demonstrated track record applying AI to real engineering work across design, simulation, test, or production.
Experience with startups or high-growth companies, plus a strong interest in working with founders and small teams that move quickly.
Strong technical communication skills, including the ability to translate AI concepts into architectural decisions and actionable implementation plans for both software and hardware audiences, and to lead technical workshops, hackathons, or developer-focused events.
A collaborative approach and the ability to move across domains quickly (robots to chips to rockets to factories), with a passion for making powerful technology safe and beneficial.

Compensation and benefits

Competitive compensation and benefits
Optional equity donation matching
Generous vacation and parental leave
Flexible working hours
A lovely office space for collaboration with colleagues
Guidance on Candidates' AI Usage: Learn about the policy for using AI in the application process

Logistics

Location: San Francisco, CA (hybrid). Current expectation: staff are in one of the offices at least 25% of the time, though some roles may require more.
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Visa sponsorship: Anthropic sponsors visas, and if an offer is made, they will make reasonable efforts to get you a visa with support from an immigration lawyer.
Annual salary: $280,000 - $320,000 USD

View full job page →

Applied Ai Data Jobs

Lead AI Engineer

Mid-Level AI & Machine Learning Engineer

Legal AI Engineer, Litigation

Applied AI Engineer, Startups (Physical AI)

Get Applied Ai Data Jobs alerts