Remote Machine Learning / AI Engineer

Job Title: Remote Machine Learning / AI Engineer

Location: Remote

Experience Level: Mid to Senior-Level

Job Summary:

• We are looking for a highly skilled and self-motivated Remote Machine Learning / AI Engineer to join our growing team. In this role, you will design, build, and deploy machine learning models that drive intelligent features and automation across our products. You will work closely with data scientists, software engineers, and product teams to develop end-to-end ML solutions—from data preprocessing and model training to deployment and monitoring. This is a fully remote position that offers the flexibility to work from anywhere while contributing to impactful, real-world AI applications.

Responsibilities:

• Design, build, and deploy ML/AI models to solve real-world problems.
• Work with data scientists and engineers to preprocess and clean large datasets.
• Optimize and scale ML pipelines for performance and efficiency.
• Integrate ML models into production systems via APIs or embedded systems.
• Conduct experiments and A/B testing to validate model performance.
• Stay current with the latest ML/AI research and industry trends.
• Collaborate with cross-functional teams across product, engineering, and design.
• Contribute to model monitoring, logging, and maintenance strategies.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, or related field.
• 3+ years of experience in applied machine learning or AI development.
• Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Experience with cloud platforms (AWS, GCP, or Azure) and ML tools (e.g., SageMaker, Vertex AI).
• Strong understanding of ML algorithms, data structures, and performance optimization.
• Experience working with structured and unstructured data.
• Excellent problem-solving and communication skills.
• Comfortable working in a remote and collaborative environment.
• Preferred Qualifications:
• PhD in a related field.
• Experience with MLOps tools (e.g., MLflow, Kubeflow, Airflow).
• Knowledge of NLP, computer vision, or time-series analysis.
• Experience deploying models via Docker and Kubernetes.
• Contributions to open-source AI/ML projects.
• Benefits:
• Fully remote work environment with flexible hours.
• Competitive salary and equity options.
• Health, dental, and vision insurance (country-specific).
• Learning and development budget.
• Equipment allowance.
• Collaborative and inclusive culture.