Job Summary

Global MNC Tech is seeking a highly skilled Staff Machine Learning Engineer (Modeling) to join our advanced AI and data science team. In this role, you will lead the design, development, and deployment of cutting-edge machine learning models that power scalable products and services across multiple domains. You will work closely with research scientists, software engineers, and product teams to deliver high-impact solutions, optimize model performance, and drive innovation across our technology stack.

This is a senior-level position ideal for candidates who thrive in fast-paced, collaborative environments and are passionate about applying ML research to real-world, large-scale systems.

Key Responsibilities

• Lead the end-to-end development of machine learning models, from data collection and preprocessing to model design, training, evaluation, and deployment.

• Collaborate with cross-functional teams to define product requirements and translate them into ML solutions.

• Develop and optimize scalable ML pipelines, ensuring high performance and low-latency deployment in production environments.

• Mentor and provide technical guidance to junior ML engineers and data scientists.

• Research and implement state-of-the-art algorithms in deep learning, NLP, computer vision, and other modeling areas.

• Analyze model performance and proactively identify opportunities for improvement.

• Maintain high standards of code quality, documentation, and reproducibility.

• Contribute to open-source projects and internal knowledge sharing initiatives where relevant.

Required Skills and Qualifications

• Advanced degree (Masters or PhD) in Computer Science, Statistics, Mathematics, or related fields.

• Extensive experience in machine learning and modeling techniques, including supervised, unsupervised, and reinforcement learning.

• Strong programming skills in Python, and familiarity with ML frameworks such as TensorFlow, PyTorch, or JAX.

• Experience with data engineering tools and pipelines, including SQL, Spark, or similar platforms.

• Proven track record in deploying ML models to production in cloud environments (AWS, GCP, Azure).

• Solid understanding of algorithms, data structures, and software engineering best practices.

• Strong problem-solving abilities and a research-oriented mindset.

Experience

• Minimum 7–10 years of experience in machine learning, AI research, or data science roles.

• Demonstrated experience in leading large-scale ML projects from concept to deployment.

• Experience mentoring and leading teams of engineers or scientists.

• Prior experience in a global tech company or fast-growing technology startup is preferred.

Working Hours

• Full-time position with flexible working hours.

• Some overlap with global teams may require occasional early mornings or late evenings.

• Remote work possible, with optional on-site collaboration as needed.

Knowledge, Skills, and Abilities

• Expertise in model development, evaluation metrics, hyperparameter tuning, and feature engineering.

• Strong analytical and mathematical skills, with the ability to interpret complex datasets.

• Excellent communication and collaboration skills to work across technical and non-technical teams.

• Ability to manage multiple projects simultaneously while meeting deadlines.

• Strong business acumen to align ML initiatives with organizational objectives.

Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance plans.

• Generous retirement and stock options packages.

• Flexible work arrangements and unlimited PTO policy.

• Professional development and training opportunities.

• Wellness programs, including gym memberships and mental health support.

Why Join

At Global MNC Tech, you will join a world-class team shaping the future of artificial intelligence. We value innovation, diversity, and collaboration, offering a platform to work on impactful, large-scale ML solutions that reach millions of users worldwide. As a Staff Machine Learning Engineer, your expertise will directly influence strategic decisions and technological advancements across the company.

How to Apply

Interested candidates should submit:

1. A detailed resume highlighting relevant experience.

2. A cover letter outlining your interest in the role and key achievements.

3. Links to GitHub, publications, or portfolio work if applicable.