AI/ML Engineer

We are hiring aSenior AI/ML Engineerwho brings strong experience acrossData Science, Data Engineering, and Generative AI/LLM development . This role will work on end-to-end AI solutions — from building datasets and pipelines, to developing LLM applications, to deploying models in production. Candidates may come from either aData Scientistbackground, aData Engineerbackground, or ahybrid AI/ML engineeringbackground.If you have strong experience with LLMs, Generative AI systems, data pipelines, or applied machine learning, we want to speak with you.What You Will Do ---------------------------------------------------------------------------------------- LLM & Generative AI Development Build, fine-tune, and evaluate LLMs for chatbots, agents, summarization, classification, and automation workflows Design prompt engineering, prompt chaining, and RAG (retrieval-augmented generation) pipelines Implement embeddings, vector search, and hybrid search workflows Conduct model evaluation using quantitative and qualitative metrics Prototype and ship applied AI solutions that solve real business problemsMachine Learning & Data Science Perform data exploration, feature engineering, hypothesis testing, and modeling Build predictive and classification models using modern ML techniques (transformers & classical ML) Create datasets for model training, fine-tuning, and evaluation Build dashboards, insights, and analytics to support product decisionsData Engineering & ML Infrastructure Build scalable ETL/ELT pipelines for ingestion, transformation, and model readiness Integrate data from APIs, databases, cloud services, and unstructured sources Prepare vectorization pipelines for RAG and LLM applications Support deployment of AI/ML models using APIs, containers, and microservices Develop monitoring, logging, CI/CD and automated workflows for stable production systemsCloud, Storage & Performance Work with Azure/AWS/GCP for storage, compute, and networking Manage SQL/NoSQL databases, warehouses, and data lakes Optimize pipelines, improve reliability, and ensure scalability Maintain performance dashboards and observability tools⭐ Ideal Candidate Profile ---------------------------------------------------------------------------------------- You may fit one (or more) of these backgrounds:Core Technical Skills Strong Python programming skills Strong SQL skills (data modeling, queries, optimization) Experience with cloud platforms ( Azure preferred , AWS/GCP also welcome) Experience with APIs, data ingestion, logs, and structured + unstructured data Experience supporting large-scale AI/ML workloads and production systemsLLMs & Generative AI Hands-on experience withOpenAI ,Llama ,HuggingFace ,Anthropic , or similar LLM providers Strong understanding of transformers, NLP fundamentals, embeddings, and tokenization Experience withRAG , vector search, and embeddings Familiarity with vector databases ( Pinecone ,FAISS ,Chroma , etc.) Ability to design, evaluate, and optimize prompts and LLM workflows Experience building chatbots, agents, summarizers, classifiers, or GenAI automation toolsMachine Learning & Statistical Foundations Solid grounding instatistics ,probability , andmachine learningconcepts Experience building and validating ML models (traditional ML or deep learning) Ability to evaluate model performance using quantitative and qualitative metrics Experience preparing datasets for training, fine-tuning, and evaluationData Engineering & Pipelines Experience building and maintainingETL/ELTpipelines Strong data modeling, schema design, and data quality practices Experience integrating data from APIs, DBs, cloud systems, and external sources Experience with pipelines for embeddings, vectorization, and model preparation Familiarity with streaming/real-time systems (Kafka, EventHub) is a plusML Ops & Infrastructure Familiarity with ML Ops tooling and workflows (CI/CD, testing, monitoring) Experience deploying models via REST APIs, Docker, containers, or microservices Ability to design stable, scalable, and reliable AI/ML infrastructure Experience with GPUs, compute optimization, or distributed systems is a plusEnd-to-End AI/ML Engineering Comfortable working across bothmodel developmentanddata/infrastructure Ability to design and deliver end-to-end solutions from ingestion → processing → model → deployment Strong problem solver who can translate business needs into technical architecturesRequired Skills ---------------------------------------------------------------------------------------- 3–7+ years of experience in Data Science, Data Engineering, ML Engineering, or AI Engineering Strong Python skills Experience with LLMs, Generative AI, or ML modeling Understanding of cloud environments (Azure/AWS/GCP) Experience with SQL, APIs, and data modeling Ability to turn business problems into technical architectures✨ Nice-to-Have ---------------------------------------------------------------------------------------- Experience fine-tuning LLMs (LoRA, QLoRA) Experience deploying models on GPUs Experience with Kubernetes, Docker, Terraform/Bicep Familiarity with streaming systems (Kafka, EventHub) Experience with multi-agent workflowsHow to Apply ---------------------------------------------------------------------------------------- If you're passionate about building real AI systems — not just prototypes — and want to work on impactful, production-grade solutions, we’d love to hear from you. Please share your resume at thowzif.abdullah@resunconsulting.com or apply here with your resume.