Senior AI Engineer

ZipRecruiter
Wakefield
2 weeks ago
Applications closed

Related Jobs

View all jobs

Senior AI Engineer - Remote - LegalTech - Circa. £120k

Senior AI/ML Engineer - Crypto/Blockchain

Senior AI/ML Engineer - Crypto/Blockchain

Senior AI/ML Engineer - Crypto/Blockchain

Senior AI Engineer - Remote - LegalTech - Circa. £120k

Senior AI Engineer - Remote - LegalTech - Circa. £120k

Job Description

Senior AI Engineer: C-4 Analytics

C-4 Analytics is a fast-growing, private, full-service digital marketing company that excels at helping automotive dealerships increase sales, increase market share, and lower cost per acquisition. We are currently hiring for a Senior AI Engineer as we look to expand our team and support our growing roster of local clients.

Who We're Looking For: Senior AI Engineer - Remote

We are seeking an AI Wizard who speaks fluent LLM and dreams in Vector Databases. As a Senior AI Engineer, you will be working with the latest in AI technology, including agent libraries, advanced LLMs, and NLP tools. You'll have the opportunity and autonomy to lead the development and implementation of AI-powered solutions. This role will focus on integrating diverse data sources, refining AI interactions through prompt engineering, and collaborating with cross-functional teams to drive artificial intelligence adoption and innovation. Your work will directly impact how automotive dealerships operate and compete in their markets.

If you've ever wanted to:

  • Be the person who makes AI actually useful (not just another chatbot that tells jokes)
  • Work with cutting-edge tech without the "we're changing the world with blockchain" nonsense
  • Build systems that impact real businesses and real people
  • Never have to explain to your family why you're "still playing with computers" (because the results speak for themselves)

A day in the life of a Senior AI Integration Engineer:

  • Working with NLP that utilizes cutting-edge AI technologies to integrate AI-driven insights across company systems, enhancing access to data and supporting decision-making processes.
  • Leverage AI technologies (LLMs) to continue development and implement chatbot agents for company-wide insights.
  • Implement test-driven prompt engineering to design, optimize, and refine prompts for accurate and relevant AI-driven interactions.
  • Integrate AI with internal and external data sources, ensuring seamless access to business-critical data.
  • Collaborate with engineering, data science, product management, and operations teams.
  • Assist in data architecture, preparation, and sanitization for effective use by AI models.
  • Develop AI strategies aligned with business goals and objectives.
  • Monitor and optimize AI performance for continuous improvement.
  • Advise on AI adoption and identify areas for efficiency and innovation.
  • Ensure ethical use of AI, maintaining data security, privacy, and compliance.
  • Stay current with advancements in AI, ML, and LLM technologies.

The Tech Toybox includes:

  • Modern AI Frameworks | Advanced LLMs & NLP tools
  • TensorFlow/PyTorch for those deep learning dreams
  • Cloud platforms to make it all float
  • Langchain & LlamaIndex for connecting the dots

What you’ll need to succeed:

  • At least 3 years of proficiency in AI and machine learning technologies, particularly LLMs.
  • Strong experience with prompt engineering and NLP tasks.
  • Proven experience integrating AI systems with data platforms (databases, data lakes, APIs).
  • Familiarity with data wrangling and preparation tools.
  • Programming skills in Python and experience with AI frameworks (TensorFlow and PyTorch).
  • Experience with cloud platforms (AWS, Google Cloud, etc).
  • 3+ years of professional experience working in agile teams and SDLC for AI projects.
  • Knowledge of LangChain, LangGraph, LlamaIndex, Vector Databases (i.e., OpenSearch, ElasticSearch), RAG, ETL.

This role requires a blend of technical expertise, strategic thinking, and collaborative skills to effectively integrate AI solutions and drive business value.

Flexibility:

The Senior AI Engineer may benefit from the flexibility to work in a way that suits them best. We offer the following working options:

  • Office-Based: Our modern and well-equipped office space provides a collaborative environment where you can work closely with teams.
  • Remote: We support remote work arrangements, allowing you to work from the comfort of your own home.
  • Hybrid: For those who prefer a balance between office and remote work, we offer a hybrid model.

Compensation:

We offer a competitive compensation commensurate with experience and qualifications. The starting annual on-target earning for this position is $150,000.00. The final salary will be determined based on factors such as skills, knowledge, and demonstrated expertise.

Please note that the stated salary range is flexible and negotiable based on individual qualifications and fit for the role.

Working at C-4 Analytics

We provide our employees with a range of benefits, including career development programs, unlimited paid time off, and additional perks. All are welcome to visit our careers and culture page for more details.

More About C-4 Analytics

C-4 Analytics takes the guesswork out of advertising. We provide real value to our clients because we value them as partners. We are results-driven and our strategies drive results.

Powered by JazzHR

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Tips for Staying Inspired: How Data Science Pros Fuel Creativity and Innovation

Data science sits at the dynamic intersection of statistics, computer science, and domain expertise, driving powerful innovations in industries ranging from healthcare to finance, and from retail to robotics. Yet, the daily reality for many data scientists can be a far cry from starry-eyed talk of AI and machine learning transformations. Instead, it often involves endless data wrangling, model tuning, and scrutiny over metrics. Maintaining a sense of creativity in this environment can be an uphill battle. So, how do successful data scientists continue to dream big and innovate, even when dealing with the nitty-gritty of data pipelines, debugging code, or explaining results to stakeholders? Below, we outline ten practical strategies to help data analysts, machine learning engineers, and research scientists stay inspired and push their ideas further. Whether you’re just starting out or looking to reinvigorate a long-standing career, these pointers can help you find fresh sparks of motivation.

Top 10 Data Science Career Myths Debunked: Key Facts for Aspiring Professionals

Data science has become one of the most sought-after fields in the tech world, promising attractive salaries, cutting-edge projects, and the opportunity to shape decision-making in virtually every industry. From e-commerce recommendation engines to AI-powered medical diagnostics, data scientists are the force behind innovations that drive productivity and improve people’s lives. Yet, despite the demand and glamour often associated with this discipline, data science is also shrouded in misconceptions. Some believe you need a PhD in mathematics or statistics; others assume data science is exclusively about machine learning or coding. At DataScience-Jobs.co.uk, we’ve encountered a wide array of myths that can discourage talented individuals or mislead those exploring a data science career. This article aims to bust the top 10 data science career myths—providing clarity on what data scientists actually do and illuminating the true diversity and inclusiveness of this exciting field. Whether you’re a recent graduate, a professional looking to pivot, or simply curious about data science, read on to discover the reality behind the myths.

Global vs. Local: Comparing the UK Data Science Job Market to International Landscapes

How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.