At Deep Abacus we are a team of talent acquisition specialists that have a passion for building well-rounded data-driven teams. We thrive on finding the best talent for the companies we partner with.

Deep Abacus

Building world-class teams in the US, Canada, and Europe across AI/ML, Growth, and Analytics with a particular focus on Natural Language Processing (NLP), Large Language Models (LLMs), and Computer Vision.

Principal Talent Consultant

Pollen is a technology company on a mission to build, curate, and deliver the best experiences all over the world leveraging a data-driven, customer-led mindset, and a network of global partners.   We have two

Pollen

Leading global hiring efforts across Data Science, Engineering, Marketing, Brand, Creative, Growth, Performance, CRM, Social, Content, Partnerships, Sales, Operations, and Inventory.

Talent Acquisition Lead

Pollen is a global technology company changing the game in live music, travel, sport, and lifestyle. Get in touch for opportunities across Data Science, Engineering, Marketing, Brand, Creative, Growth, Performance, CRM, Social, Content, Partnerships, Sales, Operations, Inventory, CX, Community, and more.

Senior Talent Acquisition Manager

Brought in-house by Pollen leadership following Series-B funding round in 2019.

Talent Acquisition Manager

Represent Talent

Recruitment Consultant

LimeLight Sports Club

- Developed strategy for holistic customer journey across major participation sports events
- Operational delivery of key experiences across multi-day, large-scale festivals (50k+ cap)
- Success measured through ongoing customer feedback loops and NPS 
- 2 direct reports and oversaw teams of 100+ at live events

Senior Experience Manager

- Ensure all company applications are considered from a customer experience standpoint 
- Creative planning through to operational delivery of key event and venue experiences
- Complex, multi-stage, live event presentation, and entertainment programming
- Channel wider Virgin brand values at every customer touchpoint

Experience Manager

- Execution of customer experience strategy 
- Concepted and executed multi-layered live entertainment programs
- Conducted RFPs and managed 3rd party agency relationships

Experience Coordinator

- Execution of multi-channel marketing plans for sold-out running events of up to 20k people
- Events included Hackney Half Marathon, London 10k, Oxford Half Marathon and more
- Aquired by Virgin Group in 2016

Marketing Executive

Sam Jacobs

Data Scientist: Python proficiency (Pandas, NumPy, etc.), strong ETL/data engineering (dbt, Airflow), modern data visualization, cloud infra experience. Focus on marketing analytics, productionizing ML models, identity resolution. Remote, visa sponsorship available. Salary: $160k-$210k. Collaborate with product teams, drive growth insights into Primer's platform.

Minkyoung K.

Ankush Prakash

Daryl Kang

### **Martech fragmentation and saturation has gone too far.**

Our world is flooded with data.
‍
In a perfect world, more data would mean better markets. Products would easily reach the customers that most need them. Buyers would get less spam and find more high-value solutions.

But our world is far from perfect.

Hamstrung by limited ad platforms and an increasingly fragmented yet siloed world of martech tools, GTM teams are forced to jerry-rig their way into scaling a growth engine. They spend hours stitching together data and tools and wasting millions on spray-and-pray campaigns. We think that’s crazy. That’s why we built Primer.

 Primer

We’re looking for a Data Scientist who has built and run marketing/growth analytics at companies like Shopify, OpenStore, Wish, OpenDoor, etc. —someone who understands what drives marketing performance and can translate that knowledge into a product. Your work won’t be about one-off dashboards or internal tools. It will be about baking high-impact growth insights directly into Primer’s platform so our customers can make better decisions at scale.This means two things:<ol><li>Deep expertise in growth &amp; performance marketing analytics – You’ve worked on problems like:<ul><li>When should performance marketers rotate creative due to ad fatigue?</li><li>What are the most successful campaigns, and how should they be optimized?</li><li>When should we use email vs. paid ads, and how should incentives be structured?</li><li>How do we detect underperforming segments before they become a problem?</li><li>How do we build the right data pipelines to answer these questions in real time?</li></ul></li><li>Strong experience in productionizing models &amp; algorithms – This isn’t an internal data role. The models you build will be a core part of Primer’s product experience. You’ll take insights and models from 0 to 1—working with messy data, developing robust models, and deploying them into a production environment used by our customers.</li></ol>But this role isn’t just about marketing analytics—you’ll also work closely with our Audiences &amp; Data team to improve data acquisition, delivery, and match rates. This means taking on challenges like:<ul><li>How do we increase data acceptance and match rates in platforms like LinkedIn and Google Ads?</li><li>How do we source and integrate new data types to expand Primer’s dataset?</li><li>How do we use deterministic and probabilistic methods to improve identity resolution and first-party data integration?</li></ul>If you love taking raw, messy data and turning it into high-leverage insights that impact strategy, this role is for you.

Data Scientist

Small in-person in SF, but most of team is remote, tend to skew towards east coast time zones

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.

Jiaqi Zhang

Ankit Khedia

Shubham Agrawal

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

AI Engineer at Mintlify. Experience in LLM fine-tuning, RAG pipelines, prompt engineering, Typescript, NodeJS, RESTful APIs. Founding/AI engineer background from top startups/universities. Empathetic, communicative, curious. On-site, visa sponsorship available. Salary: $140k-$200k. Build and integrate AI models into products.

Aashrith Sai

Sourabh Karandikar

We create public facing documentation for developers and businesses of all sizes. We're reaching 20m+ developers every year and power the documentation of 3500+ companies - recently signing X, Anthropic, Scale AI and over 20% of the last YC batch.

Co-founder

Mintlify (YC W22)

Mintlify's platform reaches 12m+ developers every year and power the documentation of 2000+ companies. We're also the #1 most popular YC product used by other YC companies in the past four years.

We already have a top of the line product for developer documentation and now we are looking at all the ways we can use AI to make it even better.Mintlify is looking for an AI Engineer to help us build, train, and optimize the first applications of AI in our product.As an AI Engineer, you will be working to fine-tune LLMs, create RAG pipelines, and understand model performance. You will work closely with the rest of the engineering team as a software engineer to integrate AI directly into our products.

AI Engineer

Open to O1, TN, or H1B transfer - cannot fully sponsor H1B

San Mateo-based, on-site, no visa sponsorship. 150k-200k. Seeking experienced engineer with Python, AWS, PostgreSQL, RESTful APIs, cloud architecture. Diverse backgrounds encouraged. Mix of startup/big tech experience preferred. Must work Mon/Wed/Fri in SF Bay Area HQ. Build scalable AI-driven marketing systems, collaborate with design/product teams.

Kelton Zhang

Justin Tinker

Tofu is an early stage generative AI startup located in the SF Bay Area (San Mateo is our HQ) building a unified platform for creating hyper-personalized, omnichannel campaigns at scale that converts leads for B2B marketing teams. We sell to mid-market and enterprise Marketing leaders and work closely with their demand generation, product marketing, and content teams.

Tofu

We're after someone who doesn't just code, but crafts. Someone who enjoys solving customer problems and gets things done end-to-end. You should excel in:<ul><li>Python, AWS services and cloud architecture</li><li>PostgreSQL and database optimization</li><li>Designing and implementing RESTful APIs</li><li>Writing clean, efficient, and maintainable code</li><li>Building scalable, distributed systems</li><li>Thinking about system design holistically</li><li>At least 4 years of working experience (mix of startup and big company experience preferred)</li></ul>Bonus points if you have experience working with AI/LLMs and knowledge of AI model deployment and optimization.

Software Engineer (Backend and ML)

Founding Engineers in SF. On-site. No visa sponsorship. $200k-$300k. Build/improve AI agents for software support. Must-have: strong CS degree, Python, pre-college coding, startup experience, AI agents/workflows, 70+ hours/week. Avoid egos. Work closely with top software companies. Fast-paced, high ownership. Proven exceptional achievements required.

Parahelp is an AI support agent for software companies. Just like a teammate, it resolves support tickets end-to-end using your existing knowledge base, SOPs, and tools (like Slack, Stripe, Retool, and Linear).

Parahelp

Parahelp is the AI support agent for software companies. Our agent resolves support tickets end-to-end by working as a coworker using a company's existing infrastructure, including tools like Slack, Stripe, Retool, Linear, etc. We're building our founding team to shape how the best software companies use AI to move faster and build better products. You'll build and improve the AI agents powering Parahelp – applying latest techniques, running evaluations, building retrieval pipelines and optimizing for speed and cost. You'll also get to work closely with customers like Perplexity, Replit, Framer, HeyGen and more. You might be a great fit if:<ul><li>You've built production-grade LLM systems and agent architectures</li><li>You have strong software engineering fundamentals and deep AI/ML knowledge</li><li>You proactively automate your own workflow with AI tools</li><li>You're ambitious and thrive in fast-paced environments</li><li>You're always trying to move faster and find shortcuts</li></ul>

Founding AI Engineer

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.

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

Full stack engineer needed at SellScale, San Francisco. On-site, 5 days/week. Must have SQL (PostgresSQL, Supabase), React/Typescript, Python (FastAPI/Django/Flask) experience. AI agent building, hackathon participation, startup enthusiasm required. No senior guidance; buck stops with you. US-based CS undergrad degree. No visa sponsorship. Salary: $120k-$180k.

At SellScale, we are building AI agentic tools for sales teams around the world. The future of sales is going to be more personal - no more mass-sequencing, shot-in-the-dark cold calling, or door knocking. With the advent of recent technologies like agentic AI, large language models, vector databases, and more - future sales teams are going to be significantly more efficient and powerful than they are today.At SellScale, we build software and AI technology that gives superpowers to go-to-market leaders and founders at high growth businesses.Right now, we are in a&nbsp;massive&nbsp;AI gold rush. The agents we’re building leverage PhD-level thinking paired with state-of-the-art GTM tools (prospecting, web intent, sequencing, etc) - to fundamentally change how companies approach their growth so they can be more intentional when effective.

SellScale

We are building an agentic prospecting. Our mission is to help companies grow with AGI.Our team is looking for a full stack engineer who can deliver premium grade products to our clients: growth teams. At SellScale, you’ll be working at the intersection of growth technology and cutting edge artificial intelligence. We use recent advancements like agentic infrastructure, gNLP, RAG, vector databases, fine-tuning, few shot learning to build tools that enable sales teams to move fast, more precisely, and deliver unprecedented results. If you love working on important, high impact problems at the frontier of technology, you will love working at SellScale.

Full Stack AI Engineer (Founding)

SellScale
At SellScale, we are building AI agentic tools for sales teams around the world. The future of sales is going to be more personal - no more mass-sequencing, shot-in-the-dark cold calling, or door knocking. With the advent of recent technologies like agentic AI, large language models, vector databases, and more - future sales teams are going to be significantly more efficient and powerful than they are today.

At SellScale, we build software and AI technology that gives superpowers to go-to-market leaders and founders at high growth businesses.

Right now, we are in a massive AI gold rush. The agents we’re building leverage PhD-level thinking paired with state-of-the-art GTM tools (prospecting, web intent, sequencing, etc) - to fundamentally change how companies approach their growth so they can be more intentional when effective.

Role
Our team is looking for a full stack engineer who can deliver premium grade products to our clients: growth teams. At SellScale, you’ll be working at the intersection of growth technology and cutting edge artificial intelligence. We use recent advancements like agentic infrastructure, gNLP, RAG, vector databases, fine-tuning, few shot learning to build tools that enable sales teams to move fast, more precisely, and deliver unprecedented results. If you love working on important, high impact problems at the frontier of technology, you will love working at SellScale.

Application Process
At SellScale, we are looking for hackers & builders who can comfortably work across the stack, find creative solutions to complex problems, and build simple and elegant products for our clients. Here are the three steps to the application process:

Take Home Assignment (2-3 hours) — Build a simple full stack application (frontend + backend). Assignment will be sent to you via email. There is a 48 hour time limit. Ideally, you shouldn’t spend more than a few hours on the assignment in total!

Technical Interview (1.5 hours) — We will go through the full stack application you built, live. We will ask you to make a few tweaks & build a few features while on the call.

Culture Interview (0.5-1.5 hours) — You’ll meet our co-founders and we’ll chat and walk through a couple non-technical problems! We’ll walk through a exercises like prototyping, discussion product feature, LLM prompting, WOZ-ing, and more.

Expectations
Here’s a couple things we’d expect from someone taking on this role:

Thorough understanding and experience with full stack development and APIs. Prior work with agent-based AI systems and LLMs is strongly preferred.

Strong Python, JavaScript, React, React Native, Flask, PSQL, and LLM-prompting skills.

Experience working with & prompting LLM APIs like OpenAI’s GPT-4 or Anthropic Claude

Fearlessly works across the entire stack (backend / frontend / design / infra / tooling )

Strong communication skills. Able to speak to contributions from both ‘technical’ and ‘non-technical’ lens

Detail oriented & fast learner. Ability to adapt and learn quickly in ambiguity.

Ability to tie all contributions to end-business outcomes and own/manage projects end-to-end

Great UI/UX intuition and able to make ‘riff’ on designs with product / design team

Work with customers to understand pain points then design + build solutions

High degrees of ownership & operational trust. Everyone on the team prefers a job where nobody cares if you need to leave for an ortho appointment in the middle of the day, but you also don’t think twice about addressing an urgent bug at 10pm while watching your favorite TV show in your PJs.

Qualifications
Strong programming skills (Python, Javascript)

Technical growth knowledge (enterprise sales, marketing software, automations, etc)

Familiarity with agent-based AI systems and LLM prompting

Familiarity with frontend technologies (React, React Native, Typescript)

Experience working in fast-paced environments where you needed to ship & learn quickly

Experience building in production environments (alerting, reporting, metrics)

Great product sense (attention to detail around customer needs)

Excited to build solutions to solve the schlep we encounter

Motivated to grow, learn & improve

Excited to work with a strong & collaborative team

At least 3+ years of professional software development experience (full stack)

Values
The Wizard of Oz - before engineering anything, we approach problems manually to understand tech and processes from first principles

Shipyard - Everything we do is tied to a client-deliverable, also known as a ‘shipyard’. We have a bias for taking action and showing proof via live deliverable to get feedback and test.

Hackathon Mentality - We operate at hackathon speed; high velocity, launch when uncomfortable, trying new things.

Disinfect with sunlight - We solve problems by first putting sunlight on the issue. If something is falling behind, there’s immediately a dashboard / channel for company-wide visibility.

We <3 Schlep - Schlep is the really boring, annoying problems everyone overlooks but it’s critical for UX. Solving Schlep at SellScale is fun!

Delta Force - A unit of A players beats an army of B players. At SellScale, we push limits of what one person can do, double down on internal talent, and hold a high performance bar.

Able to come 5 days a week in San Francisco to our office.

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.

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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