London office, Vauxhall

Full time, 5 days in office

We also have these roles Open on our Website:

1. Senior ML Engineer
2. LLM/NLP Engineer
3. Frontend Developer

Please apply only on: https://www.consigli.ai/careers

At Consigli, we build technology that makes engineering faster, smarter, and more sustainable. As a Software Developer / MLOps Engineer, you’ll work at the intersection of software engineering and machine learning operations. Your role is to ensure our AI models run reliably, efficiently, and at scale — turning cutting-edge research into production-ready tools that deliver real value to users.

What You’ll Do

1. Build and maintain robust ML pipelines for training, deployment, and monitoring
2. Develop backend systems and APIs that integrate AI into our SaaS platform
3. Take ownership of the ML performance, monitoring, availability, and security
4. Collaborate with ML engineers, data engineers, and product teams to deliver features end-to-end
5. Contribute to architecture decisions for scalable, cloud-native ML infrastructure
6. Stay up to date with the latest in MLOps practices and tools, and bring improvements into the workflow

Must-Have Qualifications

1. Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (or equivalent experience)
2. Solid programming skills in Python (plus experience with web libraries like FastAPI, Flask, or Django)
3. Hands-on experience with ML model deployment and monitoring in production Knowledge of containerization (Docker)
4. Experience with CI/CD pipelines and cloud environments (we use Azure)
5. Strong communication skills and a collaborative mindset

Preferred Skills

1. Experience with model versioning and experiment tracking (e.g. MLflow, Weights & Biases)
2. Understanding of optimizing both CPU-bound and GPU-bound workloads
3. Knowledge of monitoring and observability tools (e.g. Prometheus, Grafana, ELK stack)
4. Background in optimization, reinforcement learning, or generative AI (a plus, not required)
5. Identifying and resolving bottlenecks in distributed machine learning workloads (knowledge of low-level languages and CUDA library is a plus)

Our Hiring Process

1. Questionnaire to get a feel for your mindset and priorities
2. 15-minute screening call
3. Coding case: A hands-on task to assess your problem-solving and technical skills
4. In-person meeting with our leadership team — COO, Head of Product, and CTO
5. Final cultural fit check with our CEO

Why Join Consigli?

1. Work on real-world problems where AI creates measurable impact
2. Be part of a team where your work matters, and your ideas become real
3. Collaborate with sharp, driven colleagues in a culture of trust, ownership, and high standards
4. Enjoy a dynamic hybrid setup, balancing focus and collaboration
5. Contribute to making the built environment smarter and more sustainable