Machine Learning Engineer / Data Scientist
Machine Learning Engineer / Data Scientist at Fusemachines — Remote
- Company: Fusemachines
- Location: Remote
- Employment type: FULL_TIME
- Salary: USD 120000–180000 / year
- Posted: 2026-05-23
About this role
Machine Learning Engineer / Data Scientist
Fusemachines - Remote (US)
About Fusemachines:
Fusemachines is a leading AI solutions company that provides AI talent and education solutions to organizations worldwide. Founded with the mission to democratize AI, we partner with enterprises to build AI-powered products and capabilities.
Role Overview:
We are looking for a talented Machine Learning Engineer / Data Scientist to join our AI team. You will work on cutting-edge ML projects, designing and implementing machine learning models that solve complex business problems for our enterprise clients.
Responsibilities:
- Design, develop, and deploy machine learning models and algorithms for production systems
- Perform data analysis, feature engineering, and model selection for various ML tasks (NLP, Computer Vision, Time Series)
- Build and maintain ML pipelines and infrastructure for model training, evaluation, and deployment
- Collaborate with cross-functional teams including product managers, software engineers, and domain experts
- Research and implement state-of-the-art ML techniques and architectures
- Conduct A/B testing and analyze model performance metrics
- Write clean, well-documented, and tested code
- Present findings and insights to technical and non-technical stakeholders
- Mentor junior team members on ML best practices
Requirements:
- Master's or PhD in Computer Science, Machine Learning, Statistics, or related field
- 3+ years of industry experience in machine learning or data science
- Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn)
- Experience with deep learning architectures (transformers, CNNs, RNNs)
- Solid understanding of statistics, probability, and linear algebra
- Experience with cloud platforms (AWS, GCP, or Azure) and MLOps tools
- Familiarity with SQL and data processing frameworks (Spark, Pandas)
- Experience with version control (Git) and CI/CD pipelines
- Strong communication and problem-solving skills
Preferred Qualifications:
- Experience with large language models (LLMs) and generative AI
- Published research in top ML conferences (NeurIPS, ICML, ACL, CVPR)
- Experience with Kubernetes and containerized deployments
- Knowledge of causal inference and experimentation frameworks
Benefits:
- Competitive salary and equity compensation
- Comprehensive health, dental, and vision coverage
- Flexible remote work arrangement
- Professional development and conference attendance budget
- Collaborative, research-oriented culture