Senior Machine Learning / Platform Engineer - Agentic AIThe Talance Group • New York, New York, United States
Senior Machine Learning / Platform Engineer - Agentic AI
The Talance Group
- New York, New York, United States
- New York, New York, United States
About
The world's largest independent energy trader, moving a meaningful share of global oil supply every day, with one of the most respected names in physical commodity trading
Six decades in business and marking its 60th anniversary, with a long track record of prudent financial management through every kind of market cycle
Consistently the most profitable trader in the sector, outperforming its rivals by a wide margin even in calmer markets
Growing and diversifying well beyond oil, with fast‑expanding LNG and natural gas businesses and a newly built metals trading arm spanning iron ore, aluminium, and copper
Owned by its own people, where employee shareholders share directly in the firm's performance, so strong contributors benefit from the upside they help create
On‑site chef for breakfast, lunch and snacks – on‑site gym – massages offered close to 5 times a week
Excellent benefits and unmatched bonus and profit sharing opportunities
A firm in the energy, commodities, and trading space is seeking a Senior Machine Learning / Platform Engineer to design and build a production‑grade agentic workflow platform. This is a pivotal, high‑priority, hands‑on individual‑contributor role sitting within a core “tiger team” that is rapidly building out AI capabilities for the trading and commercial business, supporting business intelligence and analytics.
The role sits at the intersection of LLM systems engineering, distributed platforms, and applied ML, with a strong emphasis on orchestration, reliability, and extensibility. The engineer will architect and implement agent‑based workflows that integrate large language models, retrieval systems, structured knowledge, and external APIs — designed for robustness, observability, and real‑world business use.
This is not a role for someone who only does simple updates or rollouts, nor for someone purely in traditional ML/DS — the right person is actively building GenAI products day to day and can take full ownership of projects.
WHAT YOU'LL DO
Design and implement single‑agent and multi‑agent workflows using orchestration patterns and tools, context engineering, memory management, and guardrail strategies
Design RAG pipelines incorporating vector search, hybrid retrieval, and citation tracking
Implement knowledge graph–backed reasoning, including ontologies, entity resolution, and graph‑based context construction
Design evaluation frameworks for agent task‑completion correctness, quality, cost, and latency
Develop and deploy ML models with a focus on production readiness, scalability, and performance
Collaborate with data scientists to transition experimental models into robust, production‑grade applications
Integrate with collaboration platforms (e.g., Teams, alerting systems) for intelligent distribution of insights
Implement and manage CI/CD pipelines to automate deployment, testing, and monitoring
Architect and deploy systems on AWS, leveraging compute, storage, and security services
WHAT THE TEAM IS LOOKING FOR (Must‑Haves)
6+ years of experience in software, ML, or platform engineering — most recently at an O&G, commodity, or banking firm
Hands‑on individual contributor (not a lead/manager role) who takes hold of projects end to end
GenAI, LLM, NLP, and customer‑facing chatbot experience
Agentic AI focus: agent / multi‑agent architecture, orchestration, and guardrails
Platform engineering, ideally with the ability to drive the R&D of a platform
Strong proficiency writing production‑grade Python
Hands‑on with LangChain / LangGraph
Solid understanding of RAG architectures, embeddings, and vector search
Experience designing and consuming APIs (REST and/or async/event‑driven)
Strong cloud engineering experience on AWS
Exceptional teamwork, especially within a dynamic, innovative “tiger team” building early‑stage PoC systems
Bachelor's or master's in Computer Science, Engineering, or a related field
NICE TO HAVE
Experience with Claude (or comparable frontier models, e.g., Crew AI) and with Claude Code or Cursor
AWS AgentCore (or comparable agentic frameworks)
MCP and LangSmith
Knowledge of fine‑tuning frontier models to specific domain knowledge
Experience with distillation, quantization, and Small Language Models (SLMs)
MLOps experience deploying traditional ML models into production
Knowledge of distributed systems, large‑scale model optimization, container orchestration, and cloud‑native application design
Interested, or know someone who'd be a great fit? Apply or reach out directly.
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Languages
- English
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