AI/ML Engineer I
Posted Updated
Summary
Designs, develops, and deploys production computer-vision/ML solutions for retail at Everseen — owning ML components, running and presenting experiments, and moving models from research to production using Python, C++/CUDA, PyTorch, OpenCV, and Docker/Kubernetes on real-time video pipelines.
Everseen: A leader in vision AI solutions for the world’s leading retailers.
The Role
AI/ML Engineer I is responsible for designing, developing, and deploying AI/ML solutions that solve business problems and enhance product capabilities. The role collaborates with cross-functional teams to build scalable, reliable, and production-ready machine learning systems. Independently owns larger features or components and translates research ideas into efficient solutions with practical business impact. Continuously improves model performance, scalability, and operational excellence through innovation and engineering best practices.
Job Responsibilities
- Owns and delivers key ML components or features of a project.
- Presents experimental results with clarity and proposes design solutions verbally and in writing
- Designs and implements targeted initiatives to optimize production efficiency and output, operating without supervision.
- Develops advanced-scope tools to improve efficiency and reduce unnecessary complexity.
- Demonstrates understanding of how components and features impact the business, and ensures work is aligned with overall project outcomes.
- Success Indicators:
- Implements production-quality models with high performance.
- Creates reproducible pipelines and workflows.
- Collaborating with cross-functional teams and contributes to documentation.
- Languages: Python, C/C++, CUDA
- AI/ML & Computer Vision: PyTorch, OpenCV, TensorFlow, TensorRT, ONNX
- Tools & Infrastructure: Linux, Docker, Kubernetes, Git, and CI/CD pipelines
- Data: Real-time video processing, RTSP/video streaming and cloud platforms
- A minimum of 1 – 3 years in a similar role managing complex technical projects.
- Bachelor’s or Master’s degree in Engineering, Computer Science, Machine Learning or a related field is preffered.
- Deeper understanding of ML algorithms, tuning, training and evaluation procedures.
- Ability to design experiments, analyse and present results.
- Strong practical problem-solving skills.
- Strong analytical skills, able to identify trends and make decisions based on data.
- Strong data analysis and statistical reasoning.
- Capable of implementing algorithms and solutions presented in papers.
- Capable of expanding on experimental results presented by others.
- Experience moving models from research to production (latency, scalability).
- Integrate and maintain the standards of code and model quality that facilitate further research and allow for easy long-term maintenance.
- Think critically about the information they are working with and come up with efficient solutions to problems.
- Write independent research reports
Tech Stack
Profile and Skills
About Everseen
Shrink and inefficiency cost global retailers more than a hundred billion dollars each year. But Everseen is changing that equation. We are a leader in vision AI, transforming business operations for global retailers by reducing shrink, improving operations, and delivering a better customer experience.
Supporting 11 of the top 20 global retailers, Everseen’s AI innovations help retailers save millions of dollars every month. Its flagship product, Evercheck, is deployed in 10,000 retail stores and 150,000 checkouts globally. Everseen operates at unmatched scale, processing over 15 million transactions, and more than six petabytes of video data, daily.
Trusted by major food, drug, mass, and specialty retailers around the world - including Kroger, Meijer, and Woolworths - we also partner with leading hardware, AI, and cloud computing providers such as Google, NVIDIA, NCR, and Dell.
Founded in 2007 and headquartered in Cork, Ireland, Everseen has over 700 employees globally, with a European headquarters in Cork, Ireland, a U.S. headquarters in Miami, and hubs in Romania, Serbia, India, Australia, and Spain.
We are a dedicated team of inventors, research scientists, engineers, AI experts and retail industry veterans. Our culture is built on accountability, collaboration, and high standards. We take ownership of outcomes, prioritise our customers, operate as one team, move quickly with purpose, and continually raise the bar in everything we deliver.
Our Culture
Our culture is built on ownership and accountability, we own outcomes, not tasks. We stay relentlessly customer-first, letting their needs shape our priorities and decisions.
We work as one team: we challenge ideas, align quickly, and commit together. We move with pace, without compromising on simplicity or quality. And every day, we raise the bar, strengthening our talent, pushing innovation forward, and maximizing our impact.
Our Values
We OWN THE OUTCOME. No silos, no excuses.
We ARE CUSTOMER-FIRST. They guide our decisions.
We ARE ONE TEAM. Debate, decide, commit.
We MOVE WITH PACE. With simplicity and quality.
We RAISE THE BAR. On talent, innovation and impact.
Our Commitment
Everseen is committed to creating an environment where everyone can succeed. Our employees should feel a sense of belonging, have an opportunity to grow their careers, and feel free to be their most authentic selves. Everseen takes great pride in the diversity of its global workforce, and insists upon a safe, inclusive workplace where our differences are our collective strength. We treat each other with dignity, and respect, and require all employees, officers, and directors to seek to understand the importance and value to Everseen of diversity, and inclusion.
Everseen is committed to creating a safe environment for all employees and has a zero tolerance policy for bias and discrimination of any kind. Our work environment is one without offensive, hostile, or intimidating conduct, whether verbal, written or physical, in nature. Everseen will not tolerate prejudice or discrimination of any kind including without limitation, where based on aspects such as, race, colour, sex, gender, religion, age, family status, disability of any kind, sexual orientation.
