AI Engineer – Local Models, Computer Vision & RAG
Confirmed on the employer's own hiring board on Oct 2, 2026. First seen by Alion on Sep 23, 2026. Signify Technology scores C on the Alion truth index.
AI Engineer - Local Models, Computer Vision & RAG
Location: Remote, United States - Midwest-based candidates preferred
Employment type: Permanent, full-time
Salary: Targeting approximately $120,000, with some flexibility based on experience
Sponsorship: This position cannot provide current or future visa sponsorship
The opportunity
We are working with an innovative technology and entertainment business that develops advanced interactive experiences for commercial and government clients.
The company is looking for a hands-on AI Engineer to help build its internal AI capability. This is not simply an API integration role. You will train, fine-tune, deploy and optimise AI models, including running models locally on company-owned GPU infrastructure.
You will work closely with a highly experienced technical leader and take ownership of projects spanning local LLMs, computer vision, multimodal AI, RAG and secure offline deployment.
What you will be doing
Building, fine-tuning and evaluating AI and machine-learning models
Deploying and serving models locally using GPU infrastructure
Developing RAG systems using proprietary datasets, embeddings and vector search
Building computer-vision and multimodal solutions
Working with object detection, tracking and real-time model inference
Optimising models through quantisation, latency reduction and GPU-memory management
Creating APIs and integrating AI capabilities into existing applications
Developing evaluation frameworks, guardrails and hallucination controls
Supporting deployments within offline, air-gapped or security-restricted environments
Taking technical ownership from experimentation through to production
Working directly with senior technical leadership to challenge ideas and shape the AI roadmap
Essential experience
Strong commercial experience in AI, machine learning or deep learning
Advanced Python development skills
Hands-on experience training or fine-tuning models-not solely consuming hosted AI APIs
Experience deploying local or self-hosted models
Practical experience with GPU-based inference and optimisation
Strong understanding of LLMs, transformers and modern model architectures
Experience building production RAG pipelines
Knowledge of embeddings, vector databases, retrieval and reranking
Experience developing APIs and integrating models into production applications
Ability to explain clearly what you personally designed, built and deployed
Highly desirable experience
Computer vision, object detection or object tracking
Vision-language models and multimodal AI
LoRA, QLoRA or supervised fine-tuning
vLLM, Hugging Face, PyTorch or similar technologies
Model quantisation and inference optimisation
Voice AI, speech-to-text or text-to-speech
Unreal Engine, gaming, simulation or interactive technology
Real-time applications or event-driven systems
Air-gapped, on-premises or security-restricted deployments
Defence, themed entertainment or immersive-experience projects
The person
The successful candidate will be an independent and curious engineer who enjoys solving difficult technical problems. You should be comfortable challenging existing thinking, experimenting with new approaches and taking responsibility for delivering working systems, not simply producing proofs of concept.
This position offers the opportunity to join at an early stage of the company’s AI journey and play a meaningful role in defining how its internal AI capability develops.
Applicants must already be permanently authorised to work in the United States. Visa sponsorship is not available.
Accessibility Statement:?
We make an active choice to be inclusive towards everyone every day.? Please let us know if you require any accessibility adjustments through the application or interview process.??
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Our Commitment to Diversity, Equity, and Inclusion:
Signify’s mission is to empower every person, regardless of their background or?circumstances, with an equitable chance to achieve the careers?they deserve. Building a diverse future, one placement at a?time.??
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