Data Scientist / AI Engineer

Job Description

We are looking for a Data Scientist / AI Engineer who can combine strong Python programming skills, machine learning expertise, and modern Generative AI technologies to develop and deploy production-ready AI solutions. The ideal candidate has hands-on experience delivering end-to-end AI projects, particularly in LLMs, RAG architectures, and AI-powered applications, and can collaborate effectively with technical and business teams.

Key Responsibilities

• Design, develop, and deploy AI and machine learning solutions for real-world business problems.
• Build LLM-based applications using Retrieval-Augmented Generation (RAG), prompt engineering, embeddings, and vector databases.
• Develop and optimize AI pipelines, data processing workflows, and model inference services using Python.
• Take AI solutions from experimentation and prototyping to production deployment, monitoring, and continuous improvement.
• Evaluate model performance, accuracy, latency, scalability, and cost to ensure reliable production use.
• Work with structured and unstructured data to develop predictive models, NLP solutions, and intelligent applications.
• Collaborate with software engineers, data engineers, product managers, and business stakeholders throughout the project lifecycle.
• Translate business requirements into practical AI solutions and communicate technical concepts clearly to both technical and non-technical audiences.
• Follow best practices for version control, testing, API development, documentation, and maintainable code.

Requirements

• Strong hands-on experience with Python and its data science and machine learning ecosystem.
• More than 5 years of experience in the related field
• Experience developing and deploying AI/ML solutions in production environments.
• Practical knowledge of LLMs, Generative AI, RAG architectures, embeddings, and prompt engineering.
• Experience with machine learning algorithms, model training, evaluation, and optimization.
• Familiarity with frameworks and libraries such as PyTorch, TensorFlow, Scikit-learn, Hugging Face, LangChain, or LlamaIndex.
• Experience with vector databases and semantic search technologies such as FAISS, Pinecone, Weaviate, or Chroma.
• Experience developing REST APIs and integrating AI models into software applications.
• Understanding of data preparation, feature engineering, model evaluation, and data processing pipelines.
• Strong communication and problem-solving skills, with the ability to explain technical findings and recommendations clearly.
• Proven ability to take ownership of projects, work collaboratively, and deliver solutions from concept to production.

Nice to Have

• Experience with AI agents, tool calling, and multi-step LLM workflows.
• Knowledge of cloud platforms such as AWS, Azure, or Google Cloud.
• Experience with Docker, Kubernetes, CI/CD, model serving, and MLOps practices.
• Familiarity with LLM evaluation, hallucination reduction, guardrails, and observability.
• Experience with NLP, information retrieval, recommendation systems, or predictive analytics.
• Experience working directly with clients or business stakeholders to define requirements and present project outcomes.

Ideal Candidate Profile

We are looking for someone who combines the analytical mindset of a Data Scientist with the engineering capabilities of an AI Engineer. The ideal candidate has delivered real-world AI projects, understands the challenges of production environments, keeps up with emerging LLM and RAG technologies, and communicates effectively with both technical teams and business stakeholders.