Intelletec helps startups grow to their full potential, without having to worry about their hiring needs.  So what makes us different? 

1. Being right at the forefront of the industry and keeping abreast of new industries and technologies makes us stand out from the crowd.

2.  Intelletec works with VC, Angels and other industry leaders and has formed close relationships that are based on trust. 80% of our business comes from referrals!

3. All of our consultants were brought up in the new era of technology and social media, therefore we are all passionate in what we do

4. We get a real buzz helping to shape engineering teams from scratch and knowing that we can make a big difference to the success of any company we help out.

5. Being small has its pro's, most importantly being FLEXIBLE which is crucial (in the startup world). Large recruitment agencies tend to fall short of this. 

6. We now have an office in Los Angeles and a team in New York allowing us to cover more of the globe.  With two dedicated USA based teams we are still able to give all our clients a personal and bespoke service. 

To find out more about the exciting journey Intelletec are going on visit our website www.intelletec.com

Intelletec

Technical Recruiting Specialties:
- Data Science & Analytics (Junior, Senior, Lead, Staff Levels)
- Generative AI (LLMs, GANs/Diffusion Modeling)
- Data Engineering
- Machine Learning
- Research Science
- Data Science/ Analytics Leadership (Manager, Director, VP)

Managing Consultant - Machine Learning, Data Science & AI

As a Principal Consultant I work on delivering all around great experiences.

I'm here to partner with talented professionals and share rewarding and fulfilling opportunities across Data Science & Analytics, Machine Learning and AI - collaborating with some of the most exciting and progressive start-ups in the United States.

With a special focus on Data Science & Analytics we work with start-ups from (small and large) along with enterprise organizations.

Interested in connecting? Don't be shy! Reach out to me directly to learn about what we have available and how I can help!

Principal Consultant - Data Science & Analytics

Kforce is a solutions firm specializing in technology, finance and accounting, and professional staffing services. Our KNOWLEDGEforce® empowers industry-leading companies to achieve their digital transformation goals. We curate teams of technical experts who build solutions custom-tailored to each client’s needs. These scalable, flexible outcomes are shaped by deep market knowledge, thought leadership and our multi-industry expertise.

Our integrated approach is rooted in 60 years of proven success deploying highly skilled professionals on a temporary and direct-hire basis. Each year, approximately 18,000 talented experts work with a majority of the Fortune 500. Together, we deliver Great Results Through Strategic Partnership and Knowledge Sharing®.

Kforce Inc

Talent Director - Senior Technical Recruiter

ESPN is the leading multiplatform sports entertainment brand that features seven U.S. television networks, the leading sports app, direct-to-consumer ESPN+,

ESPN

- Assisted with the production of the “Green and Gold Today” show
- Cut up & cleaned audio using Cool Edit Pro and uploaded to ESPNwisconsin.com via stationcaster
- Assisted in various marketing campaigns and promotional activities across Milwaukee
- Interviewed various local college coaches and players and compiled a podcast as final project
- Tasked with creating marketing plans and outreaching to local community

Show & Marketing Intern

ISM is the global leader in sports hospitality, dedicated to helping companies foster and strengthen client relationships. Since 1997 we've worked with over 750 Fortune 1000 companies, as well as many

International Sports Management, Inc. 

Account Executive

Adam Oliver Brown

Adam Brown

Rohan J. Dani

Arno Murcia

Olena Bogdanov

Neel B.

Extend is building the next generation document processing cloud. We're enabling ambitious technical &amp; product teams to turn their messy documents into a competitive advantage.Extend is used in production at companies like Brex, Opendoor, Checkr, Vendr, and more. Our customers use our platform to turn their mountains of unstructured data (documents, PDFs, emails, images) → insights, customer NPS, operational efficiency, or new product initiatives.We're powering mission-critical data processing at companies where if we get things wrong, there are real world impacts (e.g. missed payments, people can't move into homes on time).Here's a few of the complex technical problems we're working on:<ul><li>How do we enable enterprises to deploy AI agents into production with confidence?</li><li>How do we handle never before seen edge cases in customer data?</li><li>How do we build a self-correcting system that automatically gets better over time?</li><li>How do we enable non-technical domain experts to train AI agents with their expertise &amp; business logic?</li><li>How do we help customers make tradeoffs between latency, cost, and performance?</li><li>How do we build reliable systems that can process large data streams in real-time?</li></ul>

Co-Founder & CTO

Extend

Extend is enabling enterprises to deploy in-house AI agents for processing unstructured data. As an AI Engineer at Extend, you’ll design novel techniques, systems, and human ↔ AI interfaces for building LLM agents that operate on complex data streams. We’re looking to hire engineers who think creatively about problems, keep up to date on the latest in AI research, push for real-world customer impact (not only theory), and are excited about empowering organizations with AI.We're powering mission-critical data processing at companies where if we get things wrong, there are real world impacts (e.g. missed payments, people can't move into homes on time).Here's a few of the complex problems you’ll be working on:<ul><li>How do we build a self-correcting system that automatically gets better over time?</li><li>How do we enable non-technical domain experts to train AI agents with their expertise &amp; business logic?</li><li>How do we deploy non-deterministic AI into mission-critical flows?</li><li>How do we help customers make tradeoffs between latency, cost, and performance?</li></ul>

Senior AI Engineer

About the role
Extend is enabling enterprises to deploy in-house AI agents for processing unstructured data. As an AI Engineer at Extend, you’ll design novel techniques, systems, and human ↔ AI interfaces for building LLM agents that operate on complex data streams.

We’re looking to hire engineers who think creatively about problems, keep up to date on the latest in AI research, push for real-world customer impact (not only theory), and are excited about empowering organizations with AI.

IMPACT
We're powering mission-critical data processing at companies where if we get things wrong, there are real world impacts (e.g. missed payments, people can't move into homes on time).

Here's a few of the complex problems you’ll be working on:

How do we build a self-correcting system that automatically gets better over time?
How do we enable non-technical domain experts to train AI agents with their expertise & business logic?
How do we deploy non-deterministic AI into mission-critical flows?
How do we help customers make tradeoffs between latency, cost, and performance?
ROLE
Design novel LLM techniques for increasing the complexity of use cases and data streams that Extend can be applied to
Monitor existing agents in production, understand what’s working well (and what isn’t), and run experiments to solve those issues
Implement the best human ↔ AI interfaces for designing data processing agents. We are building a new territory of UX that previously did not exist. It’s up to us to discover and implement new patterns that work for our users.
Have complete ownership over the work you do — as a founding team member, you’ll have the opportunity to truly own large areas of product and engineering and have direct relationship with customers.
Work directly with the CEO, CTO, and other founding members and help build out our team.
About Extend
Hi! We're Extend, and we're helping companies deploy in-house AI agents for processing unstructured data. Extend is used in production at companies like Brex, Opendoor, Checkr, Vendr, and more. Our customers use our platform to build, deploy, and monitor intelligent data processing agents to turn their mountains of unstructured data (documents, PDFs, emails, images) → insights, customer NPS, operational efficiency, or new product initiatives.

We're powering mission-critical data processing at companies where if we get things wrong, there are real world impacts (e.g. missed payments, people can't move into homes on time).

Here's a few of the complex technical problems we're working on:

How do we enable enterprises to deploy AI agents into production with confidence?
How do we handle never before seen edge cases in customer data?
How do we build a self-correcting system that automatically gets better over time?
How do we enable non-technical domain experts to train AI agents with their expertise & business logic?
How do we help customers make tradeoffs between latency, cost, and performance?
How do we build reliable systems that can process large data streams in real-time?
TEAM
We're a small team of 5 that's fully in-person in NYC. Our backers include Homebrew, Innovation Endeavors, Character, and angels from OpenAI, Brex, Airbnb, Newfront, and more.

Customer-Facing Machine Learning Engineer in Menlo Park, CA. On-site/Remote, Visa sponsorship available. Requires 3+ years deep learning in production, 2+ years customer-facing experience, strong ML/AI skills. Work with enterprise clients to develop LLM solutions using Lamini platform. Blend technical expertise with customer collaboration. $150K-$200K salary range.

Akshay Punhani

Suman Tripathy

Hariom Vyas

Lamini makes it possible for enterprises to turn proprietary data into the next generation of LLM capabilities, by offering a platform for in-house software teams to uplevel to OpenAI-level AI teams and to build within the security of their existing infrastructure.

Lamini

Lamini enables every enterprise to safely, quickly, and cost-effectively build their own Expert AI. Our customers own their own models, trained on their data. Lamini optimizes for Expert AI workloads with minimal hallucination, enterprise-grade security, and enterprise flexibility, running on any infrastructure. Our team is made up of highly committed engineers, researchers, and tech industry veterans excited by mission and technology. We’re backed by leading VCs as well as computing and technology companies.As a Customer-Facing Machine Learning Engineer, you’ll work directly with enterprise customers to leverage Lamini platform to develop and deploy LLM solutions that drive business value. This role blends technical expertise, customer collaboration, and problem-solving to ensure customers achieve maximum benefit from our platform. You will play a pivotal role in bridging the gap between our engineering team and customers, providing technical support, gathering feedback, and leading implementation efforts.

Machine Learning Engineer - Customer Facing

Can sponsor TN, H1B, H1B Transfer, visa renewals

First machine learning engineer needed to build intelligence layer for data activation products. Must have experience in ML, modeling, backend engineering, distributed systems, and LLMs. Strong backend and ML principles required. Remote work, visa sponsorship available. Salary: $200K-$260K. Report to Ernest.

Ryan Najafi Arman

Zac Liu

Hightouch’s mission is to empower everyone to take action on their data. Through our Reverse ETL platform, business and data users can seamlessly sync data from where it resides, such as warehouses and databases, to where it is needed, including operational systems and SaaS tools. Traditionally, acting on data has required engineering time and bandwidth, and left most business users stuck with charts and reports that are unable to take automated action on their data. With Hightouch, every business user, without writing any code, can activate data to streamline critical processes, improve marketing performance, and scale operations. Our team operates with a focus on making a meaningful impact for our customers. We believe in approaching challenges with a first principles thinking mindset, moving quickly and embracing our value of efficient execution, and treating each other with compassion and kindness. We look for team members that are strong communicators, have a growth mindset, and are motivated and persistent in achieving our goals.Hundreds of companies use Hightouch, including Spotify, Ramp, Retool, NBA, Plaid, and Betterment. We’re based in San Francisco, are remote-friendly, and backed by leading investors such as Amplify Partners, ICONIQ Growth, Bain Capital Ventures, Y-Combinator, and Afore Capital.

VP of Engineering

Hightouch

We’re looking to hire our first machine learning engineer as we expand our data activation products to include an intelligence layer. While hundreds of companies use Hightouch today to sync data into their SaaS systems to automate and improve operations, there’s a lot of surface area we haven’t touched in helping companies figuring out which customers to message, what content to put in messages, and when to send messages. A lot of this work today is done manually through intuition and guesswork, and we believe that adding machine learning could have a step function impact for our customers. And given our access to data warehouses and databases, Hightouch is perfectly placed to make use of a company’s customer data in building a powerful intelligence layer.As our founding machine learning engineer, you will help build comprehensive solutions to the above domains from scratch. Responsibilities will be highly varied and include working on customer research, problem definition, predictive modeling, machine learning infrastructure, and partnering with customers.

Machine Learning Engineer, AI Decisioning

**SF Hybrid (3-5 days in office)**. No visa sponsorship. $130k-$200k. **Key Requirements**: Must handle startup pace, have solid understanding of ML algorithms, especially multimodal LLMs. Experience fine-tuning, deploying LLMs, shipping high-quality code, cloud environments (AWS, Google, Azure). Strong communication, collaboration skills. **Responsibilities**: Build AI models/features impacting business, focus on document extraction/understanding, workflow automation. End-to-end ML model experience essential.

Anrui (Allie) Gu

Loop is on a mission to unlock profits trapped in the supply chain&nbsp;(<a target="_blank" rel="noopener noreferrer nofollow" href="https://loop.com/article/unlock-profit-trapped-in-your-supply-chain">https://loop.com/article/unlock-profit-trapped-in-your-supply-chain</a><a target="_blank" rel="noopener noreferrer nofollow" href="https://loop.com/article/unlock-profit-trapped-in-your-supply-chain)">)</a>&nbsp;and&nbsp;lower costs for consumers. Bad data and inefficient workflows create friction that limits working capital and raises costs for every supply chain stakeholder.Loop’s modern audit and pay platform uses our domain-driven AI to harness the complexity of supply chain data and documentation. We improve transportation spend visibility so companies can control their costs and power profit. That is why industry leaders like J.P. Morgan Chase, Great Dane, Emerge, and Loadsmart work with Loop.Our investors include J.P. Morgan, Index Ventures, Founders Fund, 8VC, Susa Ventures, Flexport, and 50 industry-leading angel investors. Our team brings subject matter expertise from companies like Uber, Google, Flexport, Meta, Samsara, Intuit, Rakuten, and long-standing industry leaders like C.H. Robinson.

Loop

Loop is growing its AI team and you’ll have the opportunity to build both AI models and features that directly impact Loop’s business. Loop is positioned to disrupt the incumbent freight audit and pay market, and is one of the companies leading the <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.8vc.com/resources/the-ai-services-wave-lessons-from-palantir-in-the-new-age-of-ai">AI services wave</a>, utilizing AI to automate complex back-office workflows and tasks. You will face and solve many complex technical challenges while you receive guidance and feedback from the team. The range of work here is broad, you can work on everything from training and deploying in-house multimodal LLMs, scaling our inference infrastructure, or building out and shipping AI agent workflows. In doing so, you’ll have the opportunity to define how the AI and broader Loop team will grow.&nbsp;What you will work onOur primary focus has been on document extraction and understanding, where we utilize multimodal LLMs to extract, normalize, and link data together into our domain model. As Loop’s customers rely on Loop to ingest and normalize highly accurate data, we hold ourselves to a high standard to build models with a very high level of accuracy. In tandem, Loop’s machine learning platform requires a high degree of reliability and scalability, and we expect our training and inference volume to scale several orders of magnitude in the coming year. Going forward, Loop will expand its AI capabilities, expanding into other areas such as workflow automation and audit, where we will utilize agents to tackle these problems.&nbsp;This role spans multiple domains:<ul><li>ML modeling – training, evaluating, and deploying models.</li><li>ML infrastructure – scaling data infrastructure, training, or inference, improving reliability of ML systems at Loop.</li><li>AI engineering – utilizing and orchestrating API LLM models to solve business problems at Loop.</li><li>Backend engineering – building out atomic tasks, general backend work in the servicing or automation domain.</li></ul>Some projects you might work on:<ul><li>Scaling up throughput of Loop’s inference engine through continuous batching.</li><li>Developing ways to fine-tuning multimodal LLMs to reduce hallucinations.</li><li>Build out agents that audits freight invoices.</li></ul>

AI Engineer

Based in San Francisco office. Expectation of 3-5 days per week in office. Flexible on specific days but regular in-person presence expected.

Experienced software engineer needed in San Francisco for hybrid work. Must have 5+ years in startups, strong frontend/backend skills, and proficiency in Node.js, TypeScript, GraphQL, PostgreSQL. AI/ML API experience preferred. Build AI automation in logistics. No visa sponsorship. Salary: $200-270k.

Nikita Voloshyn

Pallet is a company dedicated to disrupting the logistics industry providing end-to-end logistics visibility, control, and optimization. Our flagship product is a cartage Transportation Management System (TMS) designed to streamline business operations. We've eliminated data entry, integrated warehouse management, automated billing processes, and more. Our TMS and Warehouse Management System (WMS) offer the tools to enhance logistics operations, reduce costs, and improve customer satisfaction with faster and more reliable delivery times for carriers. Join us on our journey to transform the logistics industry and be a part of the future of business growth with Pallet.

Pallet

As an AI Agents Software Engineer at Pallet, you will be at the forefront of developing intelligent, adaptable automation solutions for the logistics industry. Our AI-driven agentic workflows are designed to augment human capabilities, handling complex back-office tasks with high accuracy while integrating seamlessly into existing enterprise systems.You will be working with a small, high-impact team of engineers and operators to build AI agents that automate workflows such as document processing, customer portal updates, and voice-based interactions. This is an opportunity to make a direct impact on a rapidly growing product with significant industry traction.What You'll Be Working On<ul><li>Developing AI-Powered Automation: Build intelligent agents that can navigate web portals, process documents, and handle voice-based interactions with human-like accuracy.</li><li>Enhancing System Adaptability: Enable AI agents to learn from human supervision and dynamically adjust to changing workflows, applications, and data structures.</li><li>Scaling AI Workflows: Ensure our AI-driven automation systems can handle high-volume logistics processes across multiple industries with reliability and efficiency.</li><li>Seamless Enterprise Integration: Design and implement APIs, database solutions, and front-end interfaces that connect our AI agents with enterprise software stacks.</li><li>Driving Performance &amp; Accuracy: Optimize AI models for speed, accuracy, and scalability, ensuring human-in-the-loop supervision enhances rather than bottlenecks efficiency.</li></ul>What You Bring<ul><li>5+ years of Software Engineering experience, ideally with exposure to both startup and enterprise-scale engineering environments.</li><li>A track record of delivering impactful business outcomes through innovative product development or high-impact technical initiatives.</li><li>Experience leading engineering teams, mentoring junior engineers, and fostering a culture of collaboration and innovation.</li><li>Proficiency in Node.js, TypeScript, GraphQL, PostgreSQL, and related technologies.</li><li>A problem-solving mindset and a passion for building intelligent, scalable automation solutions.</li></ul>

Founding AI Agents Engineer

Qingchen Wang, Ph.D.

Melange is a venture-backed startup building a brand new search infrastructure for the patent system. Leveraging recent and ongoing advancements in machine learning and natural language processing, we are building systems to conduct patent search faster and more accurately than any human currently can. We are a small team with a friendly, mostly-remote culture. The company is well capitalized, having raised 9.1 million dollars in a Series Seed led by Greenoaks Capital.

Melange

At Melange, we are using LLMs to build a tool that will help lawyers and examiners evaluate the validity of any patent with greater accuracy at a fraction of the cost.Leveraging recent and ongoing advancements in machine learning and natural language processing, you will be building systems to conduct patent search faster and more accurately than any human currently can. We are a small team with a friendly, mostly-remote culture. The company is well capitalized, having raised 9.1 million dollars in a Series Seed led by Greenoaks Capital.

Machine Learning Scientist

It's only in person in New York as we have an office. But we have employees in Los Angeles, San Francisco, Austin, and Boston.

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