AI/ML Engineer I

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. Tech Stack 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 Profile and Skills 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
• Implements production-quality models with high performance.
• Creates reproducible pipelines and workflows.
• Collaborating with cross-functional teams and contributes to documentation.

Tech Stack

Profile and Skills

• 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

About Everseen