Senior AI Engineer

About CyOpsPath

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Key Responsibilities

• AI & ML Development: Architect, fine-tune, and deploy advanced machine learning models, deep learning architectures, and generative AI systems.
• Production Engineering: Build end-to-end AI pipelines for model training, testing, continuous integration, and real-time inference.
• Optimization & Performance: Optimize model efficiency, latency, and throughput for high-availability systems.
• Cross-Functional Collaboration: Partner with data engineers, product managers, and backend teams to define AI architecture and data requirements.
• Mentorship & Quality: Establish best practices for ML code quality, evaluation frameworks, and system monitoring.

Qualifications & Requirements

• Experience: 4+ years of hands-on experience in software engineering, with at least 2–3 years focused on building and deploying machine learning or AI models in production.
• Technical Skills: Proficiency in Python and modern AI/ML frameworks (e.g., PyTorch, TensorFlow).
• AI Specializations: Strong experience with LLMs, NLP, RAG architectures, computer vision, or predictive modeling.
• Cloud & MLOps: Hands-on expertise with cloud platforms (AWS, Azure, or GCP) and MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes).
• Data Systems: Solid understanding of data pipelines, SQL, vector databases (e.g., Pinecone, Milvus), and Big Data concepts.
• Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related technical field.