Machine Learning Developer

Role & responsibilities

• Collaborate with data engineers and domain experts to develop and maintain robust data

pipelines for large-scale image and sensor datasets.

• Conduct exploratory data analysis and apply statistical modeling to derive insights that

support R&D and business strategy.

• Partner with technology teams to integrate models into IGIs production systems,

ensuring reliability, interpretability, and scalability.

• Design optimization frameworks for lab workflows, sample routing, and resource

allocation to enhance operational efficiency.

• Develop and deploy computer vision and image analytics models to analyze and classify

diamonds, gemstones, and jewelry based on optical and photographic data.

• Build deep learning models (CNNs, Vision Transformers, GANs) for image-based

quality detection, inclusion mapping, color/clarity estimation, and automated grading.

• Leverage AI and data-driven insights to improve grading consistency and reduce human

subjectivity.

• Stay updated on the latest advancements in AI for imaging, optimization, and gemology, and proactively propose innovations.

Required Qualifications

• Masters or Ph.D. in Computer Science, Data Science, Applied Mathematics,

Engineering, or related quantitative fields.

• 3+ years of hands-on experience in machine learning, optimization, and computer vision.
• Expertise in Python and related frameworks: TensorFlow, PyTorch, OpenCV, and Scikit-

learn.

• Proficiency in optimization techniques (linear/non-linear programming, heuristics, or

constraint-based modeling).

• Strong analytical and problem-solving abilities, with demonstrated success translating

data-driven insights into business impact.

• Proven experience with core ML, deep learning architectures for image analysis and

visual inspection.• Experience deploying ML models on cloud platforms (AWS, Azure, or GCP).

• Familiarity with MLOps and version control practices for production-scale AI

deployment.

• Excellent communication and collaboration skills; ability to partner with technical and

non-technical stakeholders.

Preferred candidate profile