Machine Learning Engineers
Contract, Contract-to-Hire, and Direct Hire ServicesCareful Introductions By People
Who Understand Machine Learning
At ProFocus, we bring experience to the table when it comes to placing Machine Learning Engineers. Our track record of success in helping clients find the talent they need speaks for itself. With a strong background in Fortune 500 companies, we’ve consistently delivered results in critical environments, giving you the confidence that we can do the same for you.
Since 2014, we’ve been specializing in technology roles, accumulating a decade’s worth of experience and a deep understanding of the intricacies involved:
- We zero in on the right candidates. Not all Machine Learning Engineers are the same and we understand the differences. You’ll benefit when we find the right candidates and not send you the wrong ones.
- We understand your Machine Learning role may have other titles such as Data Scientist, NLP Engineer, Computer Vision Engineer, Robotics Engineer, etc. We dig in to understand the key differences.
- We have an extensive network of talent. We’re constantly engaged in filling Machine Learning roles for our clients, which ensures that our talent pool remains fresh and dynamic.
- We pay attention to the details. You need specific skills and background and culture fit. We carefully consider these in candidates and only introduce accurately matched candidates.
Our unique business approach emphasizes quality over quantity, resulting in fewer introductions but better candidates. We’re all about technology – it’s the one thing we do, and we do it exceptionally well. This focus on technology allows us to make superior candidate matches for our clients while providing a top-notch experience for our consultants.
We are not just recruiters; we are true analysts of tech job roles.
FAQ Machine Learning Professionals
What skills and experience should I look for in machine learning engineer?
How do I evaluate a machine engineer's technical skills?
ProFocus uses several technical evaluations that can include a review of their portfolio or GitHub projects, technical interviews focusing on JavaScript concepts and problem-solving skills, coding tests or challenges specific to your tech stack or project needs, and discussions about their previous projects and specific contributions.
What are common tech environments for ML engineers?
The choice of environment depends on project needs and team preferences, directly influencing productivity and project success. Some common examples that ProFocus consultants have experience with include:
- Programming Languages: Python, R, Java
- Machine Learning Frameworks: TensorFlow, PyTorch, Keras, Scikit-learn
- Development Tools and IDEs: Jupyter Notebooks, PyCharm, Visual Studio Code
- Data Processing & Storage Platforms: Apache Spark, Hadoop, SQL, NoSQL
- Cloud Computing Platforms: AWS, Google Cloud Platform, Azure
- Version Control: Git
- Containerization Tools: Docker, Kubernetes
- CI/CD Tools: Jenkins, CircleCI, GitHub Actions
What should I communicate to a staffing agency when looking for a ML engineer?
At ProFocus, we are analysts of tech roles and we will ask detail questions about your JavaScript roles like:
- Can you describe the primary responsibilities for this JavaScript Developer role?
- What specific JavaScript frameworks or libraries does the team primarily use (e.g., React, Angular, Vue.js)?
- Are there any other programming languages or technologies (e.g., TypeScript, Node.js, databases) that the developer will need to work with?
- What level of experience are you looking for (junior, mid-level, senior)?
- What type of projects will the developer be working on, and what will their role be within the team?
- How does the team manage code reviews, testing, and quality assurance for JavaScript projects?
- Are there any soft skills or particular traits that would make a candidate a great fit for your team’s culture?
- Is there a preference for candidates with experience in specific industries or types of projects (e.g., e-commerce, enterprise applications)?
- What is the expected timeline for project delivery, and what are the key milestones?
- How does this role fit into the larger goals of the technology department and the company as a whole?
What industries do staffing companies provide services for?
ProFocus provides technology professionals in a variety of industries including:
- Government
- Education
- Agriculture
- Energy / Natural Resources
- Services
- Manufacturing
- Financial / Banking / Insurance / Real Estate
- Healthcare
- Retail / E-commerce
- IT & Telecom
How can a staffing agency assist in hiring machine learning engineers?
Staffing agencies specializing in technology roles, like ProFocus, can provide access to a pre-vetted pool of candidates, significantly shortening the hiring timeline. They understand the specific skills and experience required for Machine Learning roles and can match candidates who not only meet the technical requirements but also fit the company culture.
What skill levels can staffing companies provide?
- Junior
- Mid-Level
- Senior
- Architect
- Lead
- Supervisor
- Manager
- Director
- VP
Do staffing companies provide on-site, remote, and hybrid talent?
Staffing companies typically can staff on-site or remote/hybrid. At ProFocus we have a range of offerings including:
- On-Site
- Remote
- Hybrid
- Nearshore
- Offshore
What is the difference between a machine learning engineer and a Generative AI engineer?
At ProFocus, we differentiate between Machine Learning Engineers and Generative AI Engineers based on their areas of expertise. Machine Learning Engineers are involved in a broad spectrum of tasks from data preprocessing to deploying algorithms that enable machines to learn from data and make decisions. Their expertise covers various machine-learning techniques for a wide range of applications.
Generative AI Engineers, however, specialize in creating models that generate new, realistic data similar to their training sets. They focus on advanced neural networks like Generative Adversarial Networks (GANs) and transformer models, aiming at innovative applications such as content creation and data simulation.
Overall, Machine Learning Engineers have a broad focus across multiple domains of AI, while Generative AI Engineers dive deep into the niche of generative models, a key area for creative and forward-thinking technology solutions.
Ways We Help Tech Hiring Managers
We partner with hiring managers and tech leaders to only carefully introduce talent. They trust us to introduce them to talent that matches their tech stack and culture. We support hiring managers and talent every step of the way.
Talent Satisfaction
- ProFocus Net Performer Score (NPS) 87.5%
- Average Staffing Industry 18%
Client Satisfaction
- ProFocus Net Performer Score (NPS) 83.3%
- Average Staffing Industry 41%
Award-Winning Tech Staffing & Services
