AI/Machine Learning Engineer Apprenticeship

AI/Machine Learning Engineer Apprenticeship​

What is an AI/ Machine Learning Engineer Apprenticeship?

Apprenticeship.gov defines an apprenticeship as, “An industry-driven, high-quality career pathway where employers can develop and prepare their future workforce, and individuals can obtain paid work experience, classroom instruction, and a nationally-recognized, portable credential.”

Our apprenticeship program in AI/ML engineering trains apprentices in machine learning, deep learning, neural networks, working in Python or C++. We use a learning-by-doing approach and programs mirror on-the-job requirements.

Why Run an Apprenticeship?

What you will be doing throughout the program.

Backend Software Engineer Apprenticeship

Build A Diverse Pipeline

Apprenticeships are a great way to gain diverse talent through an accessible program that allows all learners to gain high quality technical education. Bridge the gap between degrees or training programs and entry-level jobs while increasing the diversity of your talent pool and workforce.

Backend Software Engineer Apprenticeship

Decrease Costs

Lower costs of recruiting and sourcing qualified talent. Find interested and invested candidates without a skills gap and provide them with a career on-ramp.

Backend Software Engineer Apprenticeship

Get Talent with the Specific Skills You Need

Not all technical skills are equal. Apprenticeships through Qwasar are customizable to your specific needs. Work with our Learning Engineers to create a pipeline of talent with specific skills, such as machine learning for autonomous driving, deep learning for the financial industry, etc.

Backend Software Engineer Apprenticeship

Consistency and Cadence of Hiring

Generate a pipeline of talent when you need it over the entire year. Plan cohort start dates around your key hiring times and meet growth requirements.

Backend Software Engineer Apprenticeship

Improve Productivity and create an overall more profitable workforce

Training workers who are dedicated and committed to your company and already have the skills needed to be successful. Engineering managers spend less time training and instructing apprentices and more time completing projects.

Backend Software Engineer Apprenticeship

Minimize Liability Costs and Uncertainty

Skills-based training and hiring decreases uncertainty in your candidates. Have confidence your pipeline is up to scratch and able to start contributing on Day 1 to your engineering organization and teams. There is little room for error or liability with this direct route.

Did you know?

In 2019 there were just 1.5% black people in technical roles within Facebook. And if we focus on just AI-based roles we would probably find that the percentage is a lot smaller….within the range of 0.5–0.9%. Source

How Apprenticeships Feed Your Talent Pipelines

Coding bootcamps often aren’t rigorous enough in their training and their curriculum skips vital fundamentals in software engineering, such that many graduates don’t make it into apprenticeships, internships, or entry-level jobs. There can be a mis-alignment of needed skills too.

Our apprenticeships can feed your talent pipelines and provide a key opportunity for potential candidates to train in the specific skill set you need, while also bringing capable diverse candidates.

AI/Machine Learning Engineer Apprenticeship 1

How an AI/Machine Learning Engineer Apprenticeship Program Works

The specific languages and skills acquired during the technical training period are customizable depending on the most pertinent need at your company. Here’s how apprenticeship programs generally work with Qwasar:

Costs

Companies pay a recruitment fee or a training fee. Companies pay apprentice salaries which are staged based on apprentice competency, starting at 50% for the first 6 months.

Location

Training is entirely remote and online. Learners complete the training on their own devices from home.

Cohorts

Cohorts are full-time, like a job. Start dates are set based on your hiring needs and cycles.

Responsibilities

Apprenticeships are a collaboration between us and your company.

What You Do
  • Announce the Apprenticeship program publicly, promote on social
  • Onboard apprentices like you do new employees after they complete the training period
  • Place apprentices into software teams with one assigned SWE who will mentor the apprentice (like a Sr SWE who works with a Mid or Junior Engineer)
  • Provide ongoing input on desired skills in apprentices
  • Communicate the program to your rejected job applicants who are of interest to your company
What We Do
  • Advertise and recruit apprentices
  • Manage, train, and prepare apprentices during training period and throughout their apprenticeship
  • Run daily standups, pair programming, and tea meetings during training periods just like engineers do on the job
  • Develop a refined training track if necessary to train in specific skills required for your positions
  • Announce the co-branded program

AI/Machine Learning Engineer Apprenticeship Curriculum

The initial training period is split into 2 tracks, followed by on-the-job training. On-The-Job training is part of any apprenticeship or internship.

Apprentices will write ~30-50K lines of code during their training period, largely in low-level languages. They will then specialize in the languages/tools of interest to your company. You can also assign a specific project (e.g. a fintech project, a game development project, a project specific to your industry) if you think it’s appropriate to eventually becoming a FTE or providing greater value on the job or on a particular team.

The apprenticeship curriculum is entirely project-based, requires building multiple software projects that respect norms and pass code reviews, and covers:

Low-level Intensive

Specialization

On-The-Job Training

Hard Skills

  • Python, Pytorch, Jupyter
  • Large & complex datasets
  • Tensorflow
  • Optimization
  • Advanced algorithms

Hard Skills

  • Python
  • Pytorch
  • Jupyter
  • C++
  • Advanced algorithms
  • CUDA
  • Tensorflow

Hard Skills

  • Neural networks (RNN, CNN)

Soft Skills

  • Inference & abstraction
  • Determination
  • Efficient debugging
  • Rigor
  • Structured problem solving
  • Pair programming
  • Self-management

Soft Skills

  • Advanced software architecture
  • Database design and development

Soft Skills

  • Technical interviews
  • Behavioral interviews
  • Resume and LinkedIn profile review

Looking for a specific language or tool that’s not here? Not a problem. Contact us to discuss options.

AI/Machine Learning Engineer Apprenticeship Timeline

Qwasar’s AI/Machine Learning Engineer Apprenticeship program generally takes 7-19 months to complete in total. Here’s an overview of how long it takes for us to recruit learners, conduct applicant interviews, then produce apprentices who are ready to feed your talent pipelines:

Backend Software Engineer Apprenticeship

How Learning Works

Learning at Qwasar is based on 21st-century learning models, not on knowledge transfer.
Here’s an overview of how learning works:

Competency-based Education

Mastering the key competencies of low-level programming is at the core of our curriculum. Our learning system is designed around what learners are capable of doing. You cannot progress in your track unless you have fully understood the concept.

Project-based Learning

Students are to complete progressively more difficult and complex software projects that build key hard skills, knowledge, and understanding, as well as soft skills such as problem-solving and creativity. Projects are rigorous, difficult, and require code reviews.

Standups, Meetings, and Pair Programming

We treat apprentices as if they were on our engineering team: they do standups, pair programming, code reviews, discuss architecture together, etc. Apprentices don’t sit in lectures or watch instructor videos: they CODE and build ML models!

Community

Learning happens in community with fellow students and Qwasar program participants. Our platform builds a supportive learning community to help students own their transition into tech industry roles.

Learning by Doing

Being a ML engineer isn’t something you’ll learn by reading a book or watching a video. You need to DO it! Learning by doing has been scientifically proven to be a superior way of learning, but more importantly, it’s a method that simulates the workplace and prepares students for jobs.

High Developer Standards

Learners are expected to deliver projects to professional standards, meaning work is client-ready. We expect this of our learners because you expect this of your employees, and our goal is to train job-ready candidates with the skills to succeed.

What to Expect From Our Software Engineer Apprentices

There are minimum table-stakes capabilities expected of software engineers. Our apprentice graduates are trained to surpass these requirements. Here’s what you can expect from your software apprentices:
  • Able to write quality code to a norm that’s readable and maintainable
  • Able to give and receive peer code reviews
  • Able to pair program and work with/on a team of engineers
  • Resourceful when it comes to finding a solution
  • Not afraid of tackling a new subject
  • Able to learn a new language or tool quickly, on their own
  • Able to actively contribute to discussions on software or data architecture
  • At ease using Git and version control systems, including in group/team projects
  • Ready to contribute to your engineering team from Day 1
  • Competent in internet research techniques
  • Able to translate a project description into an architecture, code base, and deployed solution
  • Determined problem solvers
  • Experience writing code in low-level languages while dealing with trade-offs
AI/Machine Learning Engineer Apprenticeship​
AI/Machine Learning Engineer Apprenticeship​

What Sets Our Apprenticeship Program Apart From Other Programs

Qwasar runs apprenticeships to provide a pipeline of skilled software talent to various companies, while maintaining affordable programs and attracting learners from a huge variety of backgrounds. 
  • Actually train to the high entry-level requirements for AI/ML engineer roles
  • Accessibility
  • Able to deliver a diverse population without compromising on technical abilities
  • High conversion rates of candidates & retention rates years later
  • Quality of candidates
  • The level we demand of our apprentices, because you demand a high level
  • Time spent coding and practicing everything that you’re expected to do on the job

Did you know?

No other apprenticeship provider trains in AI/Machine Learning engineering. No one offers Tensorflow, deep learning, using large and complex data sets, or offer specializations using CUDA. We don’t compromise on the technical level, because you need competent engineers to build your models!

AI/Machine Learning Engineer Apprenticeship​

What Sets Us Apart

What makes Qwasar programs different from other tech training options out there? Find out how we stack up.

AI/Machine Learning Engineer Apprenticeship​

Recruit From Us

Looking to hire graduates from Qwasar programs? Learn more about recruiting options and how to get involved.

AI/Machine Learning Engineer Apprenticeship​

Contact Us

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