Jobs

• Lead architecture and hands-on implementation of a production RAG / knowledge platform
• Build document ingestion for Google Workspace, PDFs, scans, tables, and images
• Implement permission-aware retrieval with ACL enforcement at query time
• Build hybrid search, embeddings, reranking, and citation-backed generation
• Deploy and benchmark open-weight models using vLLM or similar infrastructure
• Build evaluation/regression systems for retrieval, answer quality, security, and model upgrades
• Own production deployment, observability, CI/CD, documentation, and handoff
• Work directly with Eventum’s senior team and client technical leadership

• 6+ years of professional software/ML engineering experience
• Strong experience building production LLM/RAG systems
• Excellent Python/backend engineering skills
• Hands-on experience with embeddings, vector search, reranking, and document pipelines
• Experience serving open-weight LLMs with vLLM, SGLang, Triton, TGI, or similar
• Strong cloud/infrastructure skills; Azure, Docker, Terraform/Kubernetes, and CI/CD are especially relevant
• Experience with LLM evaluation and production reliability
• Comfortable owning ML, backend, data, and infrastructure rather than working in a narrow specialty

• Google Workspace APIs and permissions
• pgvector/Qdrant
• BM25 + dense retrieval
• OCR/document AI
• multimodal models
• Prometheus/Grafana
• no-egress or security-sensitive environments

• Develop and maintain interactive dashboards in Apache Superset
• Write and optimize complex SQL queries, create data marts
• Customize dashboards (Jinja, CSS, Python)
• Implement AI/ML solutions for analytics and forecasting
• Interact with clients, gather requirements, and present results

• Higher technical/IT education
• At least 2 years of experience as a BI developer
• At least 1 year of experience with Apache Superset
• Advanced SQL skills
• Experience with PostgreSQL/ClickHouse/MS SQL
• Knowledge of Python (Pandas, SQLAlchemy)
• Understanding of DWH and data modeling

Optional requirements:
• Experience in AI/ML analytics
• Power BI/Tableau
• Airflow
• Experience in pharmaceuticals or public sector

• Design and build multi-agent systems
• Integrate LLMs with internal tools and services
• Develop backend services and APIs for agent workflows
• Implement RAG pipelines and tool/function calling
• Build CLI-based agent workflows and automation tools
• Build computer vision pipelines: object detection, multi-object tracking, person re-identification
• Develop multi-camera multi-person tracking across camera networks
• Work with real-time video streams and GPU inference optimization

• Node.js ecosystem (Express.js)
• Python
• Experience with LLM APIs and prompt engineering
• Experience with RAG, tool calling, or agent frameworks
• Familiarity with Docker, Linux, and Git
• PyTorch and OpenCV
• Object detection and multi-object tracking (YOLO, ByteTrack / BoT-SORT or similar)
• Person re-identification and vector search (Milvus / FAISS)
• Video processing: ffmpeg / GStreamer, RTSP, hardware decoding

• NLP, ML experience
• Open-source LLM deployment or inference optimization
• Vision-language models (VLM)
• TensorRT / ONNX Runtime

• Design, train, fine-tune, evaluate, and implement generative models for applications with images, video, text, and multimodal data
• Improve visual quality of image and video generation: prompt adherence, spatial alignment, character and object consistency, temporal consistency
• Research and implement methods for controlling LLM: instruction tuning, structured generation, constrained decoding, tool usage, safety mechanisms, preference optimization
• Create evaluation systems for LLM: instruction execution, reliability, factual accuracy, tool usage accuracy, robustness against adversarial prompts
• Optimize training and inference pipelines for latency, throughput, memory usage, and infrastructure costs
• Build scalable data processing, training, fine-tuning, and real-time inference pipelines
• Integrate generative models into production systems in collaboration with engineers
• MLOps: automate testing, deployment, monitoring, rollback, and model retraining
• Analyze recent research in generative AI and assess its practical value

• At least 3 years of experience in machine learning and software development
• Extensive hands-on experience in developing/deploying generative AI models
• Deep understanding of diffusion models and image/video generation architectures
• Experience with LLM: prompting, fine-tuning, evaluation, structured outputs, tool invocation
• Hands-on experience with PyTorch or TensorFlow
• Experience transitioning models from prototype to production, operating inference services
• Experience deploying models on GPU servers and cloud platforms
• Strong Python skills and software development: testing, monitoring, debugging, optimization

• Experience with RLHF, DPO, reinforcement learning, instruction tuning
• Experience with constrained decoding, function call

• Oversee the full order assembly cycle including processes, staffing, operational quality, training, and onboarding
• Manage e-commerce assortment representation and content to ensure customer visibility of available products
• Scale operations by connecting existing stores and launching e-commerce in new locations
• Define requirements for the order assembly app and collaborate with IT and product teams for its development
• Manage the P&L of the operations department, overseeing order cost and unit economics
• Analyze reporting, dashboards, and operational metrics for e-commerce
• Lead a team of regional and operational managers (10+ people)
• Facilitate cross-functional collaboration with retail, logistics, commerce, and IT departments

• 3+ years of experience in operations management in e-grocery, e-commerce retail, or express delivery
• Experience managing a team of at least 10 people, including second-level managers
• Practical knowledge of order cost management and unit economics
• Experience with dark stores or in-store assembly at a scale of thousands of orders per day
• Understanding of courier logistics including slots, promises, routing, batching, and working with 3PL/aggregators
• Proficient in data analysis and BI systems
• Experience in setting tasks for IT/product teams