Senior AI and ML Engineer

Responsibilities:

• Lead AI Development: Own the end-to-end design, development, and operation of production-grade AI/ML solutions, including ML and NLP models, LLM, RAG, and multi-agent systems: Make key architectural decisions across model selection, training strategies, retrieval mechanisms, orchestration layers, and infrastructure.
• AI done right: Create evaluations and define metrics of success using cutting-edge AI platforms.
• MLOps: Implement and manage MLOps practices to streamline the deployment, monitoring, and maintenance of models in production environments.
• Collaboration and Leadership: Work closely with software engineers, data scientists, and product teams to align AI capabilities with business needs.
• Mentorship and Coaching: Guide and support more junior AI engineers, fostering a culture of learning and knowledge sharing.

Requirements:

• BSc/Master's degree in Computer Science, Machine Learning, Data Science, or a related field.
• Hands-on experience in LLM-powered production applications or ML/NLP applications.
• Strong proficiency in Python and AI frameworks.
• Strong understanding of machine learning fundamentals (supervised/unsupervised learning, optimization, model evaluation).
• Solid experience with NLP systems (text classification, embeddings, retrieval systems, semantic search, etc. ).
• Hands-on MLOps experience: reproducible pipelines, experiment tracking, automated evaluation, monitoring, and CI/CD for models and AI artifacts.
• Solid understanding of AI model fine-tuning, optimization, and evaluation.
• Proven experience with AWS and cloud-based AI deployments.
• Strong communication skills in English, capable of explaining complex AI concepts to technical and non-technical stakeholders - we believe in learning by sharing.
• Knowledge of reinforcement learning, retrieval-augmented generation (RAG), and multi-agent AI architectures.
• Strong data intuition: ability to inspect raw logs, design metrics, and quickly identify quality regressions.
• Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment.

Strong Plus:

• Strong AWS (or equivalent cloud platform) experience for scalable AI infrastructure.
• Experience optimizing models for latency, throughput, and cost.
• Experience fine-tuning large language models.
• Familiarity with multi-agent systems and orchestration frameworks.
• Experience designing AI systems in enterprise or B2B environments.

Skills

LLM, ML, NLP, RAG, large language model, machine learning, natural language processing, python, retrieval augmented generation