AI/ML Engineer

We are hiring a Senior AI/ML Engineer who brings strong experience across Data 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 a Data Scientist background, a Data Engineer background, or a hybrid AI/ML engineering background.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 DevelopmentBuild, fine-tune, and evaluate LLMs for chatbots, agents, summarization, classification, and automation workflowsDesign prompt engineering, prompt chaining, and RAG (retrieval-augmented generation) pipelinesImplement embeddings, vector search, and hybrid search workflowsConduct model evaluation using quantitative and qualitative metricsPrototype and ship applied AI solutions that solve real business problemsMachine Learning & Data SciencePerform data exploration, feature engineering, hypothesis testing, and modelingBuild predictive and classification models using modern ML techniques (transformers & classical ML)Create datasets for model training, fine-tuning, and evaluationBuild dashboards, insights, and analytics to support product decisionsData Engineering & ML InfrastructureBuild scalable ETL/ELT pipelines for ingestion, transformation, and model readinessIntegrate data from APIs, databases, cloud services, and unstructured sourcesPrepare vectorization pipelines for RAG and LLM applicationsSupport deployment of AI/ML models using APIs, containers, and microservicesDevelop monitoring, logging, CI/CD and automated workflows for stable production systemsCloud, Storage & PerformanceWork with Azure/AWS/GCP for storage, compute, and networkingManage SQL/NoSQL databases, warehouses, and data lakesOptimize pipelines, improve reliability, and ensure scalabilityMaintain performance dashboards and observability tools Ideal Candidate Profile----------------------------------------------------------------------------------------You may fit one (or more) of these backgrounds:Core Technical SkillsStrong Python programming skillsStrong 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 dataExperience supporting large-scale AI/ML workloads and production systemsLLMs & Generative AIHands-on experience with OpenAI, Llama, HuggingFace, Anthropic, or similar LLM providersStrong understanding of transformers, NLP fundamentals, embeddings, and tokenizationExperience with RAG, vector search, and embeddingsFamiliarity with vector databases (Pinecone, FAISS, Chroma, etc.)Ability to design, evaluate, and optimize prompts and LLM workflowsExperience building chatbots, agents, summarizers, classifiers, or GenAI automation toolsMachine Learning & Statistical FoundationsSolid grounding in statistics, probability, and machine learning conceptsExperience building and validating ML models (traditional ML or deep learning)Ability to evaluate model performance using quantitative and qualitative metricsExperience preparing datasets for training, fine-tuning, and evaluationData Engineering & PipelinesExperience building and maintaining ETL/ELT pipelinesStrong data modeling, schema design, and data quality practicesExperience integrating data from APIs, DBs, cloud systems, and external sourcesExperience with pipelines for embeddings, vectorization, and model preparationFamiliarity with streaming/real-time systems (Kafka, EventHub) is a plusML Ops & InfrastructureFamiliarity with ML Ops tooling and workflows (CI/CD, testing, monitoring)Experience deploying models via REST APIs, Docker, containers, or microservicesAbility to design stable, scalable, and reliable AI/ML infrastructureExperience with GPUs, compute optimization, or distributed systems is a plusEnd-to-End AI/ML EngineeringComfortable working across both model development and data/infrastructureAbility to design and deliver end-to-end solutions from ingestion → processing → model → deploymentStrong problem solver who can translate business needs into technical architectures Required Skills----------------------------------------------------------------------------------------3–7+ years of experience in Data Science, Data Engineering, ML Engineering, or AI EngineeringStrong Python skillsExperience with LLMs, Generative AI, or ML modelingUnderstanding of cloud environments (Azure/AWS/GCP)Experience with SQL, APIs, and data modelingAbility to turn business problems into technical architectures Nice-to-Have----------------------------------------------------------------------------------------Experience fine-tuning LLMs (LoRA, QLoRA)Experience deploying models on GPUsExperience with Kubernetes, Docker, Terraform/BicepFamiliarity with streaming systems (Kafka, EventHub)Experience with multi-agent workflows How 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.