Machine Learning Engineer

Job Title: Machine Learning Engineer (Remote)

Location: Remote – USA

Job Type: Full-Time

Salary: $130,000 – $170,000 per year (depending on experience)

Department: Engineering / AI & Data Science

About the Role:

We are seeking a highly skilled and motivated Machine Learning Engineer to join our growing AI team. In this fully remote role, you will design, develop, and deploy machine learning models that drive innovation and deliver measurable impact to our products and services. You’ll work cross-functionally with data scientists, software engineers, and product teams to create scalable ML systems used by thousands of customers daily.

Key Responsibilities:

• Design, develop, and deploy machine learning models for production use cases, including classification, regression, recommendation, and NLP.
• Collaborate with data engineers and software developers to build data pipelines and integrate ML models into cloud-based applications.
• Optimize model performance and maintain models through retraining and performance monitoring.
• Conduct data exploration and preprocessing, ensuring quality and consistency for training models.
• Evaluate model performance using statistical metrics and A/B testing methodologies.
• Translate business problems into technical solutions, prioritizing impact and feasibility.
• Stay current with the latest research in ML/AI and assess their potential application within the company.
• Write clean, maintainable code and contribute to the development of internal ML libraries and tools.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Applied Mathematics, or related field.
• 2–5 years of experience in building and deploying machine learning models in production.
• Proficiency in Python and ML frameworks such as Scikit-learn, TensorFlow, or PyTorch.
• Experience with data processing tools such as Pandas, NumPy, and SQL.
• Solid understanding of machine learning concepts, model evaluation, and optimization techniques.
• Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
• Strong problem-solving and communication skills.

Preferred Qualifications:

• Experience with MLOps tools (e.g., MLflow, SageMaker, Vertex AI).
• Background in deep learning, computer vision, or natural language processing.
• Contributions to open-source ML projects or publications in ML research.