Job Title:
Backend Java Developer with Machine Learning (applied, production-focused)
Location
: Remote/On-site/Hybrid
About Us
:
We are a fast-growing SaaS company revolutionising healthcare operations with innovative software solutions. Our products are trusted by hospitals worldwide. With a strong focus on scalability, security, and user experience, we’re on a mission to transform healthcare workflows globally.
The Role:
We’re looking for a
Backend Java Developer with Machine Learning expertise
to join our team. You will work closely with our Tech Lead to manage the entire development cycle—from backend development to deploying to production. You’ll also oversee a team of frontend and mobile developers, ensuring seamless integration and high-quality deliverables.
This is a unique opportunity to grow and learn from an experienced architect, and become a key player in a startup environment. If you’re passionate about building scalable systems, thrive in fast-paced environments, and are ready to put in the effort to make a real impact, we want to hear from you!
Key Responsibilities
:
Java
Design, develop, and deploy backend systems using
Java
.
Manage the entire development lifecycle, from planning to production deployment.
Oversee a team of frontend and mobile developers, ensuring smooth collaboration and high-quality output.
Architect scalable and secure systems, with a focus on
AWS
cloud infrastructure.
Collaborate with the Tech Lead to learn and eventually take over critical technical responsibilities.
Troubleshoot and optimize existing systems for performance and reliability.
Ensure compliance with security best practices across all development processes.
Key Responsibilities: Machine Learning (applied, production focused)
Fine-tune and deploy pretrained computer vision models (YOLOv8, Detectron2, Roboflow, HuggingFace CV models) for:
PPE detection (helmets, harnesses, vests, boots, gloves).
Safety hazard classification (scaffolds, ladders, trenches, guardrails).
Quality defect detection (misaligned tiles, cracks, surface defects).
Implement and fine-tune NLP pipelines for:
Speech-to-text (e.g., Whisper, Vosk).
Report summarisation and corrective action suggestion (HuggingFace Transformers).
Work with the team to define data annotation workflows and manage dataset versioning.
Deploy and optimise ML models into production (ONNX, TensorRT, TF Lite) for GPU inference (cloud + on-prem).
Monitor model performance and improve accuracy with active learning and user feedback loops.
Requirements
:
5+ years professional experience as a backend engineer, with deep Java expertise (Spring Boot, JPA/Hibernate, REST APIs).
Solid understanding of distributed systems, microservices, and API design.
Proven experience managing the full development lifecycle, from development to production deployment.
Hands-on experience in applied ML (not research):
Proficiency with PyTorch and/or TensorFlow.
Track record of fine-tuning and deploying pretrained models (not just consuming APIs).
Experience in computer vision (YOLO, Detectron2, Roboflow datasets).
Experience in NLP (HuggingFace Transformers, Whisper, summarisation pipelines).
Experience deploying ML models into production systems (Docker, Kubernetes, MLOps best practices).
Ability to bridge backend and ML — integrate AI outputs into enterprise-ready APIs and workflows.
Familiarity with GPU compute (CUDA basics, training/inference optimisation).
Strong problem-solving skills, ability to work with incomplete datasets, and a “get-it-done” engineering mindset.
Deep understanding and working experience in system architecture, scalability, and security.
Ability to work independently and collaboratively in a fast-paced startup environment.
Willingness to put in long hours and go the extra mile to achieve results.
Excellent problem-solving skills and attention to detail.
Speaks clearly in English with strong ability to articulate issues and problems
Education:
Bachelor’s or Master’s degree in
Computer Science, Software Engineering, Computer Engineering, or a related technical field
. Candidates with other quantitative degrees (e.g., Electrical Engineering, Mathematics) will be considered
only if they have strong professional Java backend experience.
Nice to Have
Exposure to edge AI deployments (Jetson, Intel NUC).
What Success Looks Like (First 12 months)
Deploy production-ready APIs that power reporting workflows.
Deliver working detection models adapted to local site conditions.
Integrate speech-to-text → NLP → report pipeline into the backend.
Establish a repeatable pipeline for model fine-tuning and dataset versioning.
Support live dashboards for compliance and regulatory submissions.
Why Join Us?
Impact
: Opportunity to build a category-defining product in AI.
Ownership
: you’ll be the bridge between enterprise backend engineering and applied AI.
Growth
: chance to lead AI integration strategy across other industries (EHS, healthcare, manufacturing).
Your work will directly improve healthcare operations for hospitals worldwide.
Learning
: Work closely with an experienced Tech Lead to expand your skills.
Culture
: Be part of a small, passionate team that values innovation and collaboration.
Flexibility
: Onsite/remote/hybrid work options
How to Apply
:
If you’re ready to take on this challenge and grow with us, send your resume and a brief cover letter. Let us know why you’re excited about this role and how your experience aligns with our needs.