AI Researcher/Developer Level 7 Apprentice

Summary

Join a fast growing AI research and development company as a senior apprentice. Help shape the AI-driven economy by developing the models that matter, developing specific AI R&D skills. You will study for the level 7 Artificial Intelligence MSc-level qualification.

Wage

£28,000 a year

Minimum wage rates (opens in new tab)

wage will be reviewed annually

Training course

Artificial intelligence (AI) data specialist (level 7)

Hours

Monday to Friday, 8:30am to 4:30pm, with some flexibility.

37 hours a week

Possible start date

Friday 28 March

Duration

1 year 6 months

Positions available

1

Work

As an apprentice, you’ll work at a company and get hands-on experience. You’ll gain new skills and work alongside experienced staff.

What you’ll do at work

Design and build novel deep learning frameworks.
Prepare data to ensure that it is ready to train sophisticated models in the proper manner (removing bias and ensuring data preserves client IP).
Integrate and test output models: Ensuring that developed models meet required specifications.
Construct working inference frameworks.
Conduct ongoing research and replication of the latest AI breakthroughs.

Where you’ll work

Ascend Coworking

Chatham

ME4 4HY

Training

An apprenticeship includes regular training with a college or other training organisation. At least 20% of your working hours will be spent training or studying.

College or training organisation

TECHNICAL PROFESSIONALS LIMITED

Your training course

Artificial intelligence (AI) data specialist (level 7)

Equal to master’s degree

Course contents

Use applied research and data modelling to design and refine the database & storage architectures to deliver secure, stable and scalable data products to the business
Independently analyse test data, interpret results and evaluate the suitability of proposed solutions, considering current and future business requirements
Critically evaluate arguments, assumptions, abstract concepts and data (that may be incomplete), to make recommendations and to enable a business solution or range of solutions to be achieved
Communicate concepts and present in a manner appropriate to diverse audiences, adapting communication techniques accordingly
Manage expectations and present user research insight, proposed solutions and/or test findings to clients and stakeholders.
Provide direction and technical guidance for the business with regard to AI and data science opportunities
Work autonomously and interact effectively within wide, multidisciplinary teams
Coordinate, negotiate with and manage expectations of diverse stakeholders suppliers with conflicting priorities, interests and timescales
Manipulate, analyse and visualise complex datasets
Select datasets and methodologies most appropriate to the business problem
Apply aspects of advanced maths and statistics relevant to AI and data science that deliver business outcomes
Consider the associated regulatory, legal, ethical and governance issues when evaluating choices at each stage of the data process
Identify appropriate resources and architectures for solving a computational problem within the workplace
Work collaboratively with software engineers to ensure suitable testing and documentation processes are implemented.
Develop, build and maintain the services and platforms that deliver AI and data science
Define requirements for, and supervise implementation of, and use data management infrastructure, including enterprise, private and public cloud resources and services
Consistently implement data curation and data quality controls
Develop tools that visualise data systems and structures for monitoring and performance
Use scalable infrastructures, high performance networks, infrastructure and services management and operation to generate effective business solutions.
Design efficient algorithms for accessing and analysing large amounts of data, including Application Programming Interfaces (API) to different databases and data sets
Identify and quantify different kinds of uncertainty in the outputs of data collection, experiments and analyses
Apply scientific methods in a systematic process through experimental design, exploratory data analysis and hypothesis testing to facilitate business decision making
Disseminate AI and data science practices across departments and in industry, promoting professional development and use of best practice
Apply research methodology and project management techniques appropriate to the organisation and products
Select and use programming languages and tools, and follow appropriate software development practices
Select and apply the most effective/appropriate AI and data science techniques to solve complex business problems
Analyse information, frame questions and conduct discussions with subject matter experts and assess existing data to scope new AI and data science requirements
Undertakes independent, impartial decision-making respecting the opinions and views of others in complex, unpredictable and changing circumstances
Use applied research and data modelling to design and refine the database & storage architectures to deliver secure, stable and scalable data products to the business
Independently analyse test data, interpret results and evaluate the suitability of proposed solutions, considering current and future business requirements
Critically evaluate arguments, assumptions, abstract concepts and data (that may be incomplete), to make recommendations and to enable a business solution or range of solutions to be achieved
Communicate concepts and present in a manner appropriate to diverse audiences, adapting communication techniques accordingly
Manage expectations and present user research insight, proposed solutions and/or test findings to clients and stakeholders.
Provide direction and technical guidance for the business with regard to AI and data science opportunities
Work autonomously and interact effectively within wide, multidisciplinary teams
Coordinate, negotiate with and manage expectations of diverse stakeholders suppliers with conflicting priorities, interests and timescales
Manipulate, analyse and visualise complex datasets
Select datasets and methodologies most appropriate to the business problem
Apply aspects of advanced maths and statistics relevant to AI and data science that deliver business outcomes
Consider the associated regulatory, legal, ethical and governance issues when evaluating choices at each stage of the data process
Identify appropriate resources and architectures for solving a computational problem within the workplace
Work collaboratively with software engineers to ensure suitable testing and documentation processes are implemented.
Develop, build and maintain the services and platforms that deliver AI and data science
Define requirements for, and supervise implementation of, and use data management infrastructure, including enterprise, private and public cloud resources and services
Consistently implement data curation and data quality controls
Develop tools that visualise data systems and structures for monitoring and performance
Use scalable infrastructures, high performance networks, infrastructure and services management and operation to generate effective business solutions.
Design efficient algorithms for accessing and analysing large amounts of data, including Application Programming Interfaces (API) to different databases and data sets
Identify and quantify different kinds of uncertainty in the outputs of data collection, experiments and analyses
Apply scientific methods in a systematic process through experimental design, exploratory data analysis and hypothesis testing to facilitate business decision making
Disseminate AI and data science practices across departments and in industry, promoting professional development and use of best practice
Apply research methodology and project management techniques appropriate to the organisation and products
Select and use programming languages and tools, and follow appropriate software development practices
Select and apply the most effective/appropriate AI and data science techniques to solve complex business problems
Analyse information, frame questions and conduct discussions with subject matter experts and assess existing data to scope new AI and data science requirements
Undertakes independent, impartial decision-making respecting the opinions and views of others in complex, unpredictable and changing circumstances

Your training plan

This training plan has not been finalised. Check with this employer if you’ll need to travel to a college or training location for this apprenticeship.

Requirements

Desirable qualifications

A Level in:

Maths (grade B)

T Level in:

Computer science (grade Distinction)

Degree in:

Computer science / mathematics / physics (grade upper second class)

Let the company know about other relevant qualifications and industry experience you have. They can adjust the apprenticeship to reflect what you already know.

Skills

IT skills
Number skills
Analytical skills

About this company

Pilot Generative AI is working on the research and development of next-generation AI models and associated applications. The company is focusing on niche opportunities to research AI models which deviate from the mainstream, and to deploy highly-customised models into specific corporate and educational settings.

http://pilotgenerativeai.com (opens in new tab)

Company benefits

Company pension is included.

Disability Confident

A fair proportion of interviews for this apprenticeship will be offered to applicants with a disability or long-term health condition. This includes non-visible disabilities and conditions.

You can choose to be considered for an interview under the Disability Confident scheme. You’ll need to meet the essential requirements to be considered for an interview.

After this apprenticeship

The successful apprentice would be on a path to become an AI researcher/developer as a full time role. They would be a core member of the AI research team in the firm.

Ask a question

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