Remote Artificial Intelligence Engineer – Drive Cutting‑Edge AI Solutions from Anywhere

Join a forward‑looking tech company where you will design, develop, and deploy AI models that power next‑generation products. Work fully remote with a collaborative global team and enjoy competitive compensation while solving real‑world challenges at scale.

About the Role

As an Artificial Intelligence Engineer, you will sit at the intersection of research and product engineering. Your primary mission is to transform innovative algorithms into reliable, scalable services that enhance user experience and drive business growth. You will partner with data scientists, software engineers, and product managers to identify opportunities, prototype solutions, and ship AI‑powered features that meet stringent performance and reliability standards.

Key Responsibilities

• Design and implement machine learning models for computer vision, natural language processing, recommendation systems, and time‑series forecasting.
• Build end‑to‑end ML pipelines using Python, TensorFlow/PyTorch, and cloud‑native services such as AWS SageMaker, GCP AI Platform, or Azure Machine Learning.
• Perform rigorous experimentation, hyperparameter optimization, and statistical validation to ensure model accuracy, robustness, and fairness.
• Containerize models with Docker and orchestrate deployments via Kubernetes, ensuring low‑latency inference and high availability.
• Develop RESTful and gRPC APIs that expose model capabilities to internal services and external partners.
• Establish MLOps practices: CI/CD pipelines, automated testing, model versioning (MLflow, DVC), and monitoring (Prometheus, Grafana, Evidently).
• Collaborate with cross‑functional teams to translate business requirements into technical specifications and deliver measurable impact.
• Mentor junior engineers, conduct code reviews, and contribute to internal tech talks and knowledge‑sharing sessions.

What You’ll Achieve

In this role, you will see the direct impact of your work on product metrics such as user engagement, conversion rates, and operational efficiency. You will have the opportunity to publish internal case studies, present findings at company‑wide tech forums, and influence the strategic direction of our AI initiatives. Success is measured by the deployment of models that consistently meet SLA targets, reduce bias, and generate actionable insights for stakeholders.

Requirements

Technical Skills

• Expert proficiency in Python, including experience with NumPy, pandas, and scientific computing libraries.
• Hands‑on expertise with deep learning frameworks (TensorFlow 2.x, PyTorch) and classical ML libraries (Scikit‑learn, XGBoost).
• Strong grasp of algorithms, data structures, linear algebra, probability, and statistical inference.
• Proven experience deploying models to production using cloud platforms (AWS, GCP, Azure) and container orchestration (Docker, Kubernetes).
• Familiarity with MLOps tools and practices: MLflow, DVC, Kubeflow, Jenkins/GitHub Actions, and monitoring stacks.
• Experience working with large‑scale data pipelines (Apache Spark, Flink, or Kafka) and feature stores.
• Solid understanding of software engineering best practices: version control (Git), code review, unit testing, and documentation.

Experience & Education

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Mathematics, Physics, or a related technical discipline (Ph.D. preferred for research‑heavy projects).
• Minimum of 3 years of professional experience building, training, and deploying machine learning models in a production environment.
• Demonstrated track record of delivering AI‑driven features that improved key business KPIs (e.g., +15 % recommendation click‑through, ‑20 % fraud false positives).
• Excellent problem‑solving abilities, strong analytical mindset, and the capacity to communicate complex technical concepts to both technical and non‑technical audiences.
• Proactive learner who stays current with the latest AI research (e.g., arXiv, NeurIPS, ICML) and evaluates emerging techniques for practical adoption.

Benefits & Perks

• Competitive salary range: $110,000 – $150,000 USD per year, adjusted for experience, location, and performance.
• Fully remote position – work from anywhere with a stable internet connection; we provide a home‑office stipend for ergonomic equipment.
• Flexible working hours and asynchronous collaboration to support a healthy work‑life balance.
• Comprehensive health, dental, and vision insurance plans for you and your dependents.
• Generous paid time off, company holidays, parental leave, and sabbatical options.
• Annual learning and development budget for conferences, online courses, certifications, and technical books.
• Equity/stock‑option package to share in the company’s long‑term success.
• Wellness initiatives: virtual fitness classes, mental‑health resources, and quarterly team‑building events.
• Access to cutting‑edge hardware (GPU‑enabled workstations) and cloud credits for experimentation.