About the job
Join Devsinc as a Senior AI Engineer and leverage your 4–6 years of experience in crafting, building, and launching production-quality AI systems. We seek a candidate who merges robust machine learning principles with practical knowledge of Large Language Models (LLMs), RAG architectures, and scalable ML infrastructure.
In this role, you will take charge of the complete AI lifecycle from research and experimentation through to deployment, optimization, and monitoring. You will play a pivotal role in architectural decisions, mentor fellow engineers, and deliver applied intelligence solutions that yield tangible business outcomes.
Key Responsibilities
- Design, develop, and implement AI/ML models and LLM-based solutions to tackle real-world business challenges.
- Create scalable training, fine-tuning, evaluation, and inference pipelines for production-ready AI systems.
- Design and deploy RAG pipelines, embedding systems, and retrieval-based architectures.
- Enhance model performance through experimentation, structured evaluations, hyperparameter tuning, and advanced optimization methods (quantization, batching).
- Develop APIs, microservices, and real-time inference services to integrate AI functionalities into production settings.
- Oversee and implement MLOps workflows, including experiment tracking, model versioning, CI/CD integration, monitoring, and lifecycle management.
- Engage in system architecture discussions to ensure scalability, reliability, security, and performance.
- Deploy AI systems on cloud platforms (AWS, Azure, GCP) with considerations for cost and performance optimization.
- Investigate emerging AI technologies, including LLMs, multimodal AI, and vector search, assessing their practical use cases.
- Guide junior engineers and advocate for best practices in AI engineering and MLOps.
- Document technical designs, workflows, experiments, and project outcomes for internal knowledge sharing.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related discipline.
- 4–6 years of professional experience in AI/ML engineering roles.
- Strong proficiency in Python with hands-on experience in PyTorch and/or TensorFlow.
