Hire Machine Learning Engineers
Browse 320.9k+ verified machine learning engineer profiles on Stackforce
Amanda Wood
Product Operations & Product Analytics
at AlphaSense
Yarik Markov
Co-founder & CTO
at VOYGR (YC W26)
Enric Durany
Group Product Manager
at Google
Himanshu Dhiman
Software Automation Developer 2 - Front End
at Kinaxis
Rupali Rane
Manager - Talent Acquisition
at HDFC Bank
Pritish Mishra
Senior Software Engineer
at Xneeti OneOS
Shubham Aher
Lead Software Engineer
at Indexnine Technologies
Ravi K.
Associate Manager, Talent Acquistion
at Razorpay
Jancy Alice Challam
Human Resources Specialist
at GeoIQ
Monika Saroha
Human Resources Executive
at Finkhoz Roboadvisory
Sam K.
Director of Engineering
at MishiPay
Manvi Agarwal
Manager- Staffing
at Artech Information Systems
Aviral Bhargava
Assistant Vice President - Analytics
at EXL
Tejashree Salvi
Senior Software Developer
at BMW TechWorks India
Vidya Bhushan
Guest Speaker
at B School
Lovish Dua
Software Engineer II
at Adobe
Ujjwal Awasthi
Process Developer
at Genpact
Ankit Gupta
Manager
at Easebuzz
Rajan Yadav
Assistant Manager
at Deloitte
SMARIKA SHARMA
Silicon Design Engineer 2
at AMD
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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 320.9k+ 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 Recruiting, Business Development, Product Development, Product Strategy, Product Management, Talent Acquisition. 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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