Machine Learning Research & Engineering Specialist

🔥 1 hour ago

🌐 India, Australia, +4 more countries – Remote

🇮🇳 India – Remote 🇦🇺 Australia – Remote 🇯🇵 Japan – Remote 🇸🇬 Singapore – Remote 🇵🇭 Philippines – Remote 🇳🇿 New Zealand – Remote

⏳ Contract/Temporary

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 12%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Gramian Consulting

WebsiteLinkedInAll Job Openings

2 - 10 employees

Founded 2025

💼 Consulting

📦 Logistics

📣 Marketing

Consulting • Logistics • Marketing

Gramian Consulting is a remote-first consulting firm that connects engineering and data/AI talent with organizations through talent augmentation, recruiting, dedicated teams, and contractor management. The firm provides Data & AI services including LLM training and fine-tuning, AI agents and assistants, MLOps, and AI infrastructure, and it offers mentorship and education programs for career readiness, interview preparation, and international market orientation. Rooted in hands-on engineering and recruiting experience, Gramian helps clients scale technical teams and extract business value from AI while developing individual talent.

📋 Description

• Develop, implement, and validate machine learning models, training pipelines, inference systems, and supporting infrastructure. • Implement or modify model components, data pipelines, evaluation systems, and numerical methods using Python. • Build reproducible programmatic workflows using Python, command-line tools, and relevant machine learning frameworks. • Debug numerical, algorithmic, and system-level failures to identify root causes and implement reliable solutions. • Optimize model training and inference for memory usage, computational efficiency, throughput, and performance. • Design and execute tests to verify implementation correctness and compliance with objective performance requirements. • Review and validate challenging machine learning engineering tasks, including existing code and proposed solutions. • Use coding agents as part of the development workflow to accelerate implementation, debugging, testing, and code review while validating generated results. • Document technical approaches, implementation decisions, test results, and performance findings clearly. • Deliver high-quality, reproducible task submissions within project deadlines.

🎯 Requirements

• Master's degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline. • Strong professional or research experience in machine learning and practical ML engineering. • Strong Python programming skills, including the ability to implement, debug, test, and optimize non-trivial code. • Hands-on experience using coding agents within a Python development workflow. • Understanding of machine learning model development, training and inference workflows, and evaluation methods. • Ability to build reproducible implementations and verify correctness through systematic testing. • Strong quantitative reasoning and problem-solving skills, particularly when diagnosing numerical or computational issues. • Ability to work independently, manage technical tasks, and meet defined quality and submission requirements. • Strong written communication skills and the ability to explain technical findings. • Availability to contribute approximately 15 hours per week and begin the first task within 24–48 hours after onboarding.