Hire Machine Learning Engineers
Browse 209.8k+ verified machine learning engineer profiles on Stackforce
Rubish Gupta
Engineering Manager
at Rippling
Prachi Mahamuni
Conversion Rate Optimization Manager
at Annex Cloud
Vishal L.
Staff Software Engineer
at Ping Identity
Shinoy Sharma
Associate Product Manager
at o9 Solutions, Inc.
Vipul Kohli
Senior Product Manager
at o9 Solutions, Inc.
Debojyoti Singha
Founder
at Keplars
Neeraj Chaturvedi
Co-Founder
at OneIoT
Debjani Ghosh
Distinguished Fellow
at NITI Aayog
Arti Garg
EVP, Chief Technologist
at AVEVA
Sanku Saiteja
Associate Software Engineer
at Accenture in India
Shruti Bendre
Talent Acquisition Lead
at Capgemini
Vansh B.
President
at The Consulting Club, Dyal Singh College
Albrey Brown
Founding Sales
at Central
Piyush Kukreja
Financial Advisor
at Kukreja Finance Solutions
Basang M.
Founder & CEO
at Nova Module
Pranav Baradkar
Senior Software Engineer
at Optym
Varinder Singh
Software Developer Engineer @Samsung Electronics
at Samsung R&D Institute India - Bangalore
Syed Shamsher Ali Hussain
Member of Technical Staff
at FluidCloud
Shahar Azulay
Co-Founder and CEO
at groundcover
Gregory Mermoud
Associate Professor
at HES-SO Valais-Wallis
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Get Started FreeWhat Do Machine Learning Engineers Do?
Machine learning engineers build, deploy, and maintain ML systems that power intelligent features in products and services. They bridge the gap between data science research and production engineering, turning experimental models into scalable, reliable systems. ML engineers work with frameworks like TensorFlow, PyTorch, and scikit-learn, and deploy models using MLOps tools like MLflow, Kubeflow, and SageMaker. They handle data pipelines, feature engineering, model training, hyperparameter tuning, and production inference optimization. Companies hire machine learning engineers to build recommendation systems, natural language processing features, computer vision applications, and predictive analytics platforms. As AI becomes central to product strategy, ML engineers are among the most sought-after technical professionals.
What to Look For
- Strong Python skills with deep experience in TensorFlow or PyTorch
- Has deployed ML models to production and managed the full ML lifecycle
- Experience with MLOps tools and model monitoring in production
- Understands data pipeline design and feature engineering at scale
- Can discuss model evaluation metrics and knows when models are underperforming
- Familiar with cloud ML services (SageMaker, Vertex AI, Azure ML)
Red Flags to Watch
- Cannot explain the difference between training, validation, and test sets
- Only builds models in notebooks and has never deployed to production
- No understanding of data drift, model monitoring, or retraining strategies
- Cannot discuss trade-offs between model accuracy and inference latency
- Has never worked with large datasets or distributed training
- Cannot explain the models they've built beyond 'I used a neural network'
What Hiring Managers Say
“We needed ML engineers who could take our research models to production. Stackforce matched us with engineers who understood both the math and the engineering. Our inference pipeline now processes images 5x faster.”
Robert Y.
Head of AI, Computer Vision Startup
“Finding machine learning engineers with production deployment experience is our biggest hiring challenge. Stackforce's verified profiles showed us candidates with real MLOps experience, not just Kaggle projects.”
Shreya P.
VP of Engineering, NLP Platform
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Frequently Asked Questions
How many machine learning engineers does Stackforce have?
Stackforce currently has 209.8k+ verified machine learning engineer profiles. The pool is continuously growing as new professionals join the platform.
What are the top skills of machine learning engineers?
The most common skills among machine learning engineers include Data Science, Leadership, Software Development, Product Management, Strategy, Go-to-Market Strategy. Stackforce AI automatically identifies and verifies these skills from professional profiles.
How do I hire a machine learning engineer through Stackforce?
Sign up for a free Stackforce account, browse machine learning engineers profiles, and use AI-powered matching to find the perfect candidate. You can reach out directly through the platform with verified contact information.
Is it free to browse machine learning engineer profiles on Stackforce?
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