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

Business Development Manager

Lawrence Harvey, established in 2002, is an international recruitment business specializing in Technology recruitment. Our consultants are specialists in their specific fields of recruitment, therefore we have expert

Lawrence Harvey

I recruit across all levels including Associate, Analyst, Consultant, Manager, Director, Vice President, SVP, EVP, Managing Directors, and Executives.

Core Specialties:

*Algorithm Development 
*Artificial Intelligence/AI
*Robotics 
*Blockchain 
*Data Science/Data Scientists (Machine Learning, Data Mining, Deep Learning, Predictive Analytics, NLP)
*Digital Attribution/ Multi-touch Attribution (MTA)
*Digital Analytics
*Marketing Analytics 
*Marketing Mix Modeling (MMM)
*DMP, DSP, API 
*Blockchain
*Customer Journey
*Segmentation
*Insights 
*Big Data/Hadoop
*Cloud Specialist 
*Predictive Analytics
*Statistical Modeling ( R, SAS, Python, SPSS, Excel) 
*Data Visualization (Tableau, Cognos, PowerBI)
*Data Engineering 
*Business Intelligence
*Gaming Analytics
*IoT/ Internet of Things 
*Artificial Intelligence/AI
*People Analytics, HR Analytics, Human Resource Analytics, Workforce Analytics
*Executive Search (CEO, CAO, CDO, CMO, CSO, COO)
*Voice Analytics 
*NLP specialization 
*Product Management 
*Information Architecture

Since 1988, Maxim Healthcare Staffing has brought together the nation’s top healthcare professionals with a variety of partners. We create meaningful career opportunities for healthcare workers including nurses, allied health professionals, locum tenens, medical coders, travel nurses, and many more. Our healthcare staffing and workforce management services provide talent for hospitals, schools, government programs, correctional facilities, and managed care organizations. We are committed to our mission of connecting healthcare workers to the work that matters.

Maxim Staffing Solutions 

Recruiter

Carlie Phillips

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.

Rishabh Jain

Rahul Sharma

Ajit Vijayakumar

Vikram Poddar

Digvijay S.

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

Technical Requirements: Startup & research experience, analytical field background, full stack ML skills (Python, TensorFlow, PyTorch), expertise in NLP, Deep Learning, Anomaly Detection, Transformers. Responsibilities: Train production models for sales use cases, align strategy with performance/cost. Location: San Francisco. Work Type: Hybrid. Visa: Sponsorship available.

Alok Kothari

Nooks is a platform transforming sales reps from manual laborers to scientists.With today’s technology, sales reps shouldn’t need to manually write hundreds of emails, research hundreds of websites/linkedins, and make hundreds of calls. They should instead focus on the parts of their job that actually require people - talking to customers, being creative, and problem-solving. With a combination of AI tools, automation and real-time collaboration, Nooks can do the rest.Teams that use Nooks often see a 2-3x increase in reps’ productivity within weeks! And we’re working on adding prospecting / research workflows (to-be-announced soon!).

Nooks

The roleNote: Exact job title will be commensurate with experienceWe have an ambitious product vision in a nascent area - AI-powered realtime collaboration - so there are a ton of interesting technical challenges on our roadmap. We’re hiring our first Machine Learning Engineer. This is a role focused on implementing ML features into Nooks. Our ideal candidate will have prior experience working in industry for a business where ML is a core part of the offering.Examples of engineering problems you may touchThese are just examples, this list is non-exhaustive, and you definitely don’t need experience in all of these areas. But hopefully you find some of them exciting!<ul><li>Realtime audio AI &amp; precision/recall/latency tradeoffs (algorithms &amp; models)<ul><li>We use audio data, transcription, silence detection, and several other signals to detect whether a live phone call is a voicemail, a human, or a dial tree. Here, latency is a third factor added to the standard precision/recall tradeoff because it’s important we can detect humans quickly. Our approach involves LLM embeddings, few-shot learning, data labeling, and continuous monitoring of model performance in prod.</li></ul></li><li>Smart call funnels &amp; playbooks (data wrangling, backend eng, GPT-3, UX)<ul><li>At what point in the conversation do my reps get stuck? What are the toughest questions that we need to address? Can I “program” a playbook so that Nooks will help my team standardize toward best-practices? We’re using GPT-3 and other LLM’s to turn companies’ mostly unstructured call data into actionable strategies &amp; feedback loops.</li></ul></li><li>Conversation embeddings &amp; markov models (ML modeling)<ul><li>What does the anatomy of a call look like? If I say XYZ, what are the different ways the prospect might answer and the probabilities of each? Conditioned on the first half of the call, what do I say next to maximize the likelihood that I book a demo at the end of the call? Can we use LLM’s to generate embeddings of conversations that we can use to cluster similar conversation patterns and predict where the conversation is headed?</li></ul></li></ul>

Applied Machine Learning Engineer

Backend Software Engineer (ML) needed in San Francisco, CA. Hybrid work, 3 days in-office. Visa sponsorship available. Must have proven backend systems experience, expertise in Go/Python/Java/C++, AI product experience, cloud services (AWS/Google Cloud), strong database skills. Responsibilities: API development, scalable ML models, document processing, knowledge graph enhancement, cross-functional collaboration. Salary: $200k-$220k. Prioritize female candidates with robust backend skills.

Tapas Panda

Sangram Malekar

Infinitus is a Healthcare AI communication company that automates routine calls for leading brands. With our digital assistant Eva, healthcare companies can offload thousands of benefit verification, prior authorization, and pharmacy calls per day. Infinitus automates calls between entities such as Pharmacies, Patient Access Programs, Hospitals, Providers, and Payors, enabling the US healthcare system to spend less time on hold and more time improving the patient experience.

Infinitus Systems

Infinitus offers a unique AI platform that provides AI agents and AI copilots to automate each step in support of the patient journey.  AI agents harness digital and voice-powered AI to efficiently gather data from government and commercial payors and PBMs to save time and accelerate patient access to care.   Our AI copilot, FastTrack, enables employees to bypass tedious IVR systems and hold times in making calls to payors to save time and scale your business.  These AI agents and copilots are built on a platform that combines a highly powerful AI system with robust operational guardrails to ensure safety and compliance.

Infinitus is automating routine tedious administrative work for healthcare workers. Tens of millions of Americans are under medical debt, and over half of healthcare workers are concerned about burnout. We are working to bring down costs, get patients to care faster, and free up healthcare workers to focus on patients.We’re looking for a seasoned senior Backend Software Engineer (ML) to help build and scale the core of our innovative healthcare solutions. As our system grows to serve an increasing number of customers, support a broader range of tasks for Eva—our digital health AI Agent —and automate critical administrative workflows in healthcare, this role offers an incredible opportunity to drive impact at scale. If you know someone excited about applying AI, NLP, and cutting-edge software engineering to healthcare challenges, we’d love to connect with them.

Backend Software Engineer (ML)

We’re looking for a seasoned Backend Software Engineer (ML) to help build and scale the core of our innovative healthcare solutions. As our system grows to serve an increasing number of customers, support a broader range of tasks for Eva—our digital health AI Agent —and automate critical administrative workflows in healthcare, this role offers an incredible opportunity to drive impact at scale. If you’re excited about applying AI, NLP, and cutting-edge software engineering to healthcare challenges, we’d love to connect.
In this role, you’ll contribute to:
●	API Backend Development: Architect, scale, and optimize the APIs that form the backbone of our platform, enabling seamless integrations and data flows across our ecosystem.
●	Statistical Machine Learning: Design and implement scalable ML models to improve automation, efficiency, and accuracy in solving complex healthcare tasks.
●	Document Understanding: Advance our ability to extract and process critical information from healthcare documents to power smarter decision-making.
●	Knowledge Graph Development: Build and enhance our knowledge graph to link and structure vast healthcare data for better insights and automation.
●	Cross-Functional Collaboration: Partner closely with our NLP team to integrate advanced language models, ensuring Eva continues to excel at understanding and automating routine healthcare communications..
Infinitus is automating routine tedious administrative work for healthcare workers. Tens of millions of Americans are under medical debt, and over half of healthcare workers are concerned about burnout. We are working to bring down costs, get patients to care faster, and free up healthcare workers to focus on patients.

We're a team of ex-Googlers, startup veterans, industry and healthcare experts. We're backed by Kleiner Perkins, Coatue Management, Andreessen Horowitz and Google Ventures, along with individual investments from a selection of executives across AI and tech: Ian Goodfellow, Gokul Rajaram, Aparna Chennapragada and Qasar Younis. 
Competencies
●	Has worked across multiple tech-stacks, and thrived in collaborating with Data Science, Machine Learning, Frontend/Applications and Infra teams. 
●	Has delivered, scaled and maintained a number of highly successful enterprise or consumer products. 
●	Has led and influenced multiple teams of engineers on technical design, and implementation. 
●	Has shown entrepreneurial spirit (e.g. worked at an early stage startup, or has started and delivered on a new product from the ground-up). 
●	Has led technical excellence efforts, and recognized, and reduced tech debt while delivering customer value. 
●	Is a prolific individual contributor, who role models developing quality software and technical design. 
●	Great cross functional communicator, who partners with product managers, designers, and analysts to deeply understand the needs of our users and build a product that serves those needs. 
●	Contribute to the short and long term roadmaps, and make effective tradeoffs between impact, user experience, and a high-quality technical foundation. 
●	Improve the team and company - be an active participant in our culture (hiring, mentoring, new initiatives). 
●	Aligns with our values of: Customer Obsessed; Optimistic; Disagree+Commit; Engage Employees; See, Say, Do.
Minimum Requirements
●	Proven experience in designing and implementing scalable, robust backend systems.
●	Curiosity of machine learning concepts, algorithms and infrastructure requirements.
●	Expertise in languages such as Go, Python, Java, C++ or similar, with a focus on backend development.
●	Hands-on experience with cloud services like AWS, Google Cloud.
●	Extensive experience in designing, developing and maintaining APIs for seamless integration of backend services.
●	Strong knowledge of database technologies, both SQL and NoSQL and experience in optimizing database performance.
●	7 years of hands-on engineering experience, with demonstrated growth



Build machine learning systems for AI-driven capital allocation. Must have strong AI idea generation history, exceptional engineering skills, top school background (Stanford, CMU, Harvard), and fluency in English. Located in San Francisco, hybrid work model, visa sponsorship available. Salary: $150K-$250K.

Tamer Soliman, Ph.D.

Mana is a research lab building an artificially intelligent investor. We sell contracts to financial firms, private equity and wealth management firms, as well as VCs. We help any firm looking to optimize their workflows with AI. We are semi in stealth, but typically have very large contracts right.As we build, we are paving a path to what we hope will lead to a future with AI/automated investing.

Co-Founder & CEO

Mana

You will build the machine learning systems that power our general artificial intelligence for capital allocation. We are looking for researchers who want to discover elegant deep learning concepts and then put them into production as solutions to high-stakes, real-world problems.

Applied AI Researcher

Visa sponsorship available to exceptional candidates that don't have work rights in the US

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