Machine Learning Engineer
About
NeuroHire is building an AI-first SaaS platform that helps companies hire smarter using real data. Machine learning is at the core of how our product works — powering matching, ranking, recommendations, and intelligent automation.
We’re looking for a Machine Learning Engineer who can build systems that move beyond experimentation and into real product impact.
If you enjoy working with real-world data and shipping ML systems that scale — you’ll fit right in.
What You’ll Work On
- Build, train, and deploy machine learning models for matching, ranking, and recommendations
- Work on NLP problems like resume understanding, skill extraction, and semantic matching
- Design data pipelines and feature engineering workflows
- Collaborate with engineering teams to integrate ML models into production systems
- Optimize models for performance, scalability, and reliability
- Monitor model performance and improve using real-world feedback
- Handle noisy, real-world datasets and make them usable
- Define evaluation metrics aligned with product and business impact
What We’re Looking For
- 3+ years of experience building machine learning systems in production
- Strong foundation in machine learning, statistics, and data modeling
- Proficiency in Python and ML frameworks like scikit-learn, PyTorch, or TensorFlow
- Experience working with structured and unstructured data
- Familiarity with NLP, embeddings, or transformer-based models
- Understanding of model deployment and MLOps basics
- Strong problem-solving skills and ownership mindset
- Comfortable working in a fast-paced startup environment
Nice to Have (Not Required)
- Experience with recommendation systems or ranking models
- Exposure to LLMs or generative AI applications
- Familiarity with cloud platforms (AWS, GCP, Azure)
- Experience in SaaS or product-based companies
- Understanding of model monitoring and versioning