MLOps Engineer in Manchester

AeroCloud is the new-age operating system for airports aiming to grow. Our suite includes Airport Operating Systems (AOS), PPS, and Passenger Flow Management solutions, empowering airports to gain deep insights into the movement of passengers and aircraft around the world.

We achieve this by becoming the airport’s first call for technology. Whether in times of need or growth, we stand alongside our clients, offering support through innovative software that drives their success.

Our Commitment to Excellence

At AeroCloud, being the airport’s first call means exceeding expectations at every customer interaction. This is not just a goal; it’s our standard. We prioritize detail, diligence, and a proactive approach in everything we do. If there’s a task to be completed, we see it through. If a customer needs an answer we don’t yet have, we respond promptly to let them know we’re on it. We believe in keeping our team informed, being transparent, and maintaining accountability at every step.

About The Role

AeroCloud builds airport operations software used in production environments worldwide – you’ll be responsible for our Optic product. Optic is our computer vision product - it processes camera feeds at airports to track passenger flow, monitor zone occupancy, and feed real-time data into the broader operations platform. It runs on edge hardware, on-site at airports, and it has to work.

We're hiring one person into this role. Not a team, not a function - one engineer who owns the CV and ML capability inside Optic and knows how to operate without a safety net. The role is Hybrid, working 2 days per week from our Stockport office.

What You’ll Be Working On

• Optic sits at the physical edge of airport operations. Cameras, sensors, and inference pipelines running on hardware installed in terminals. Your work will extend what Optic can see and reason about.
• You'll work alongside software engineers on the Optic team, connect with data engineering where pipelines intersect, and operate with meaningful autonomy against a product roadmap.
• Inference pipelines running on edge hardware — latency, reliability, and resource constraints are real.
• Camera and sensor integration in physical airport environments.
• Person detection and zone-based tracking (this is live and shipping — you'll be extending it).
• New detection capabilities: baggage, vehicles, crowd flow analysis.
• Model training, evaluation, and deployment - you'll own the full loop, not just consume pre-trained models.
• Occupancy and prediction modelling connected to operational use cases.
• MLOps on Databricks - getting models from experiment to production and keeping them there.

The Stack You’ll Work With

• Python for CV and ML workloads.
• Edge deployment on AWS Greengrass.
• Databricks for model training and MLOps.
• AWS (ECS, Lambda, S3, SageMaker where applicable).
• Integration with the broader Optic platform (TypeScript/NestJS backend, MongoDB Atlas).

The Work You’ll Own

• Extending Optic's detection capabilities into new object classes and scenarios.
• Inference pipeline performance and reliability on constrained edge hardware.
• Model training workflows and deployment pipelines on Databricks.
• Technical decisions around CV architecture — and being accountable for them.
• Bridging the gap between what the hardware can see and what the product needs to know.

What We’re Looking For

• This isn't a role with mentoring baked in. The team doesn't have pairing density in this discipline - you'll be the person who sets the standard for CV and ML work at AeroCloud.
• Around 5 years of hands-on experience, with computer vision as your primary discipline, not a side interest.
• Solid CV engineering: inference pipelines, model deployment, working with real camera hardware.
• Comfortable with the full model lifecycle - training, evaluation, deployment, monitoring - not just running inference against someone else's weights.
• Experience working in production environments where things actually break and you're the one who fixes them.
• Familiar with industry-standard model formats and inference frameworks — ONNX and TensorRT in particular.
• Enough MLOps competence to ship and maintain models, not just run notebooks - Databricks familiarity is a plus.
• Understanding of model optimisation techniques such as sparsity is a plus, especially given edge hardware constraints.
• Used to operating across different problem spaces; startup or scale-up background tends to produce this.
• Able to make decisions with incomplete information and document the reasoning.

Who We’re Looking For

• You take ownership of a problem space, not just tasks assigned to you.
• You're comfortable being the only person in the room who knows this stuff.
• You care about what ships, not just what works in a notebook.
• You can explain CV and ML decisions to engineers who don't share your background.

What We Offer

• Competitive salary.
• Best in Class Share Options scheme.
• 25 days PTO + statutory holidays.
• Take your birthday off work on us as well.
• Extensive upskilling and training.
• Digital Nomad Scheme.

Our Ethos

AeroCloud recognises Diversity, Equality, and Inclusion at the heart of our business. They represent the mutual trust, respect and understanding we strive for. They are integral to our brand, reputation, success, business sustainability and employee relations impact.

Our vision is to have a diverse, equal and inclusive organisational culture. We want everyone who comes into contact with us, both face to face and virtually, to feel valued and respected. We want our workplace both in the office and at home to foster belonging to all colleagues to feel seen, connected, supported and proud. We will draw on the rich diversity of our workforce and harness the diverse contributions and considerable talents of our staff to achieve our vision in line with our organisational values and DE&I principles.

AeroCloud is an equal opportunities employer so if you have any specific work or access requirements as a result of a condition or disability then AeroCloud would be committed to working with you on the best way to support this at work.