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Machine Learning Recruiters and Executive Search

Your Machine Learning and AI Recruitment Specialists

We’re no strangers to emerging technology at Redfish. Today, machine learning and artificial intelligence experts are crucial talent for countless industries: financial trend forecasting, manufacturing management, health research, transportation development--and we’re just getting started. These tools give an organization the ability to bring order to a large amount of data, find a pattern in that information, and turn it into a prediction model for the future, improving both the end user experience and business outcomes.

Why Should You Partner with Redfish?

While a plethora of industries use machine learning algorithms, many leaders don't even know what acronyms like NLP mean, much less how to leverage that technology for their business. It's hard to set job requirements that will attract the right person if you don't even know what background and type of skills to look for during the interview process. That's where Redfish's machine learning recruitment professionals can make an impact. We understand the data science world and can spot top talent well-versed in selecting data sets that make sense for your industry, who know how to train an algorithm, avoid overfitting and underfitting to maximize its accuracy, control for bias, and develop a comprehensive AI strategy that will deliver results.

The Redfish Recruitment Process

Our team is proud to leverage the diverse creativity of the Redfish network to unlock the future. Our candidates have a passion for technology, along with expertise in statistics, data analysis, data models, and other skills crucial for success in data scientist jobs. Most importantly, we take a hands-on approach to understanding the employer's needs and preferences, using these in-depth candidate profiles as the basis of our selection process. In short, we ensure the candidate is a good fit before we send them along for an interview. As industry demands evolve at the speed of light, our dedicated ML and AI recruiters help you tackle trends and anticipate what lies ahead.

Recruit with Redfish

Redfish Technology lives at the intersection of creativity, resourcefulness, and innovation. Founded in 1996, our unique expertise in machine learning recruiting has helped grow businesses from coast to coast, with deep roots in the country’s biggest tech hubs. Are you ready to take your company to the next level?

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Join the many companies that have recruited roles with Redfish Technology

Download our 2024 salary guide

  • Salary data for all common machine learning roles
  • Includes salary adjustments for over 100 cities across the US
  • Updated for 2024
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Redfish provides tailored recruitment solutions

For high-impact leadership positions, our retained/executive search services provide premium C-suite and strategic role placement. This fully committed engagement involves close partnership with clients to understand organizational needs and long-term vision. Our executive recruiters conduct rigorous candidate assessment to ensure both skill and cultural alignment. With phased payments and dedicated resources, this model guarantees a thorough search process, resulting in strategic, high-caliber placements for these pivotal leadership positions.

The engaged recruiting model balances commitment with cost-effectiveness, providing dedicated resources to the search while reducing overall hiring costs. With a modest upfront engagement fee, we dedicate a focused team to source, screen, and shortlist candidates, ensuring a streamlined and proactive hiring process. This model is well-suited for roles that require specialized expertise or when the hiring timeline is more critical, offering clients an optimal mix of focus and flexibility.

Our contingent recruiting service is designed to provide flexibility and efficiency for companies looking to fill critical roles quickly. This model is success-based, meaning there is no fee unless a candidate is hired, making it a cost-effective solution for businesses seeking top talent without upfront financial commitment. Ideal for positions at various levels, contingent recruiting leverages Redfish’s extensive candidate network to source qualified professionals who meet the company’s requirements promptly.

Our successful searches keep our clients happy

Senior Product Manager

A long-standing client approached us seeking a Senior Product Manager to spearhead their new adtech product line. Through detailed discussions with their Director of Product, we identified the precise skill set required and quickly began sourcing qualified candidates to keep their growth initiatives on schedule. We successfully identified an ideal candidate who brought relevant industry experience and a proven track record of leading new product initiatives. Their enthusiasm for our client's vision, combined with their expertise, made them a perfect match. By managing expectations effectively throughout the process, we helped both parties achieve their preferred outcome—the client secured their top choice, and the candidate landed their desired role.

Backend Engineer

A well-funded AI startup, having secured $20M in investment, partnered with us to expand their engineering team. They needed multiple technical roles filled: several Backend Python Developers and a Frontend React Developer. Within just 12 weeks, we successfully placed three qualified engineers across various U.S. locations, helping the startup scale their development capabilities efficiently.

Chief Product Officer

A venture-backed startup's CEO sought to strengthen their executive team with a Chief Product Officer who could combine technical expertise with team leadership abilities. The role carried specific requirements: experience in Industrial AI and strong academic credentials. Within just three weeks, we identified and placed an exceptional candidate: a Johns Hopkins PhD who was serving as a hands-on VP in the industry and specifically sought an early-stage startup opportunity. This precise match fulfilled every requirement, making the search a remarkable success.

VP Engineering

Our established relationship with a CEO led to a crucial executive search at his new venture—a seed-stage data analytics company needed a VP of Engineering from a premier tech organization. Having previously built his Sales Engineering team at another startup, he trusted us with this critical hire. We delivered results within six weeks, successfully placing an exceptional candidate. This placement exemplifies the value of our long-term client relationships and our ability to execute quickly on executive searches.

We can help you hire for a variety of machine learning roles

  • Full Stack Developer/Engineer
  • Head of Software/Development/Engineering
  • ML/Ops OR MLOPS
  • Machine Learning Engineer/Developer
  • Marketing Manager
  • Platform Engineer
  • Product Manager
  • Software Engineer (Sr, Lead)
  • Solutions Architect/Engineer
  • UX Engineer/Developer
  • VP of Engineering/Vice President of Engineering

See what our clients say about our recruiting successes

Frequently asked questions about machine learning recruiting

Our engaged search process normally takes four weeks between our initial discovery call with the client and when an offer is extended. Clients get a single point of contact in our team, as well as a minimum of 20 dedicated hours each week.

The process starts with a deep dive discovery with the hiring team. This conversation focuses on two aspects: the requirements of the role and the needs and selling points of the company. Once we’ve gathered this information from the client, we use a curated four-touch candidate outreach campaign and advanced AI software to source candidates from our network. By the end of the first week, we typically have at least 5 resumes to send to clients, who get the first right of refusal on any resume sourced for their position.

Once we’ve defined the traits of the ideal candidate in our discovery call with the client, we do internal planning before going to our network. This involves separating the qualifications into “must haves” and “nice to haves”, identifying competitors that employ similar machine learning professionals, and creating a targeted four-step multi-touch campaign. We then deploy this campaign across our database and 30,000+ company followers network, leveraging our contacts as well as AI software and both paid and unpaid resources to generate qualified leads. Along the way, we provide data analysis to the client that they can use to evaluate and shape the recruiting strategy and improve the efficacy of our messaging.

We first create a list of questions that target certain skills or traits based on our discovery call with the client. As candidates are interviewed, we recalibrate with the client as necessary to make sure those questions are attracting the right candidates for their needs.

We measure our machine learning hire quality by considering factors like how many submitted candidates are interviewed, how long it took to make a placement, how long the candidate remains in the role, and feedback from clients.

We have a candidate retention rate of 86% across the industries and sectors we work with.

On average, it takes 4 weeks to fill a machine learning role.

We utilize metrics including time to hire, resumes submitted to interviews, and interview-to-hire ratio.

Working with a recruiter allows you to hire better machine learning talent more quickly, as well as saving companies the time, money, and resources they would have invested in the search. Having multiple recruiters working on a search also allows the process to be scaled, giving machine learning recruiters the capability to fill multiple roles with high-quality candidates concurrently.

The main difference comes down to the scope of the search. In a machine learning executive search, the process is more specific and targeted. More stringent criteria can mean that the search takes a bit longer, but with the result of a better long-term hire who perfectly meets the client’s needs. The payment terms are also different. With executive search, the client pays in installments throughout the process, rather than after the search is completed. Executive search firms may also charge per diems and expenses.

The network of machine learning professionals we’ve built over 30 years in the business is our biggest differentiator. Relationships are the core of this business and we always start with our network. We also have 30,000+ followers of our company that we network through.

We give them a human-focused interaction rather than a transactional one. Our goal is to build long-term relationships, and both our clients and our candidates appreciate this personal touch.

Working with a recruiter enables you to hire the best machine learning professional for the role, not just the best person in your network. The recruiting landscape has changed dramatically, and our use of AI technology, targeted messaging, and other paid and unpaid resources allows us to navigate the talent market more efficiently and at a deeper level than hiring teams can using in-house resources.

Yes, our engaged search is backed by a 60-day refund or replacement guarantee.

We start by understanding the client’s story, culture and needs through our in-depth discovery process. Next, we use this information in our screening process, and convey it to the candidates we’ve identified as a potential fit based on their skills and experience. We can also perform reference and background checks on request.

Absolutely! We want our clients and candidates to succeed, and support them throughout the hiring process. For companies, this includes helping with their job description, competitor analysis, salary ranges, and improving their interview process, as well as services like contracting, contract-to-hire, and payroll. For candidates, we help them perfect their resume and application materials and offer coaching through the interview process.

Delicately. We know the value a diverse team brings to a business and understand the crucial role recruiters play in ensuring the hiring process is free from bias. This starts by identifying areas where bias could be a factor and taking steps to ensure candidates are being fairly assessed and compared. We also observe how our clients are mitigating and preventing issues and adopt the approaches that are effective, with the goal of continuously improving the transparency, fairness, and inclusiveness of our talent sourcing and placement.

We welcome feedback from clients and candidates, and feel that full disclosure and honest, transparent communication is helpful for both sides. We also serve as a conduit for feedback between clients and candidates. If an issue is sensitive, we’ll clear it with the client or candidate before starting the conversation.

Our fee is 25% of the base first-year salary of the new hire.

No. Our fee is paid in full by the client, and there is no charge for machine learning candidates to work with us.

We maintain the confidentiality of both the hiring company and the candidates throughout the process. We sign NDAs at the start of a search and get guidance from our clients on what can and can’t be shared with candidates. All information we collect from candidates and companies is securely stored and protected from unauthorized access.

Partner with Redfish Technology