Machine Learning Engineer (MLE)

Machine Learning Engineer (Remote)

Location: Remote
Employment Type: Full-Time
Salary: Market-related (based on experience)

About the Role

We are looking for a highly skilled Machine Learning Engineer (MLE) to design, build, and deploy scalable machine learning models that drive business value. This role bridges the gap between data science and software engineering, focusing on taking models from concept to production in a reliable and efficient way.

You will work closely with data scientists, engineers, and business stakeholders to deliver impactful AI-driven solutions.

Key Responsibilities

• Design, develop, and deploy machine learning models into production environments
• Build scalable data pipelines to support model training and inference
• Optimize model performance, accuracy, and efficiency
• Collaborate with data scientists to operationalize models (MLOps)
• Monitor, maintain, and improve deployed models over time
• Implement best practices for versioning, testing, and deployment of ML systems
• Work with large datasets to extract meaningful insights and features
• Ensure models are production-ready, reliable, and secure

Required Skills & Experience

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field
• 3+ years experience in machine learning or related roles
• Strong programming skills in Python
• Experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn
• Solid understanding of machine learning algorithms and statistical modeling
• Experience with data pipelines and ETL processes
• Familiarity with cloud platforms (AWS, Azure, or GCP)
• Experience with MLOps tools (Docker, Kubernetes, CI/CD pipelines)
• Strong SQL and data manipulation skills

Nice to Have

• Experience with big data technologies (Spark, Hadoop)
• Knowledge of Deep Learning, NLP, or Computer Vision
• Experience with model monitoring and drift detection
• Exposure to LLMs / Generative AI applications
• Understanding of software engineering best practices

Key Competencies

• Strong problem-solving and analytical thinking
• Ability to work independently in a remote environment
• Excellent communication and collaboration skills
• Detail-oriented with a focus on quality and performance

What Success Looks Like

• Models successfully deployed and delivering measurable business value
• Efficient, scalable ML pipelines in production
• Continuous improvement of model accuracy and performance
• Strong collaboration across technical and business teams

Why Join

• Work remotely with a global, forward-thinking team
• Exposure to cutting-edge AI and machine learning technologies
• Opportunity to work on impactful, real-world problems
• Flexible working environment and career growth opportunities