Senior Machine Learning Engineer

Arionkoder; United States; Remote; USD 150,000 - 230,000; Full time

Benefits offered by this job

Monthly USD Service Fee

Paid Agreed Time Off

Caregiver Time Off

Dynamic remote work culture

Entrepreneurial environment

Job summary

Arionkoder, an AI consulting firm, seeks a Senior Machine Learning Engineer to own LLM-powered systems end-to-end—from rapid PoCs to production-grade solutions trusted by clients. You will operate in AI Labs, bridging engineering and data science, with a focus on eval-driven development, cost-aware design, and scalable architectures.

You will demo capabilities to clients, size pre-sales efforts, and convert learnings into reusable assets for the company.

Qualifications

• 5+ years of professional software engineering with production ownership.
• 2+ years building LLM-powered systems in production.
• Experience designing and running evals with baselines and regression thresholds.
• Advanced Python: clean, tested, typing, packaging, async.
• Hands-on MCP experience and judgment on exposing capability as a tool/server.
• Hands-on RAG experience: embeddings, vector stores, reranking.
• Experience with at least one LLM orchestration framework.
• Cloud deployment of AI/ML workloads, preferably AWS.
• CI/CD, automated tests, reproducible builds, containerization.
• Practical understanding of cost and latency engineering for LLM systems.
• Awareness of LLM security and privacy risks.
• AI-first working style with daily AI coding-tool use.
• Senior judgment: autonomous, problem framing, risk focus.
• Excellent written and spoken English; remote client-facing.

Responsibilities

• Own LLM-powered systems end-to-end from PoC to production.
• Demo live to clients; explain trade-offs to non-technical stakeholders.
• Size effort honestly in pre-sales and turn learnings into reusable assets.
• Challenge problem framing when data does not support the ask.
• Build and maintain evals, baselines, and CI-driven quality gates.
• Collaborate in a fully remote, distributed client-facing team.

Skills

Senior software engineering

LLM systems

Python

CI/CD

Cost latency engineering

Security awareness

AI tooling

Autonomous judgment

English proficiency

Tools

LangChain/LangGraph

LlamaIndex

Pydantic AI

AWS Bedrock

SageMaker

Lambda

ECS

S3

MLflow

Weights & Biases

DVC

Job description

Arionkoder is an AI consulting firm helping companies build, embed, and own AI systems that drive real business outcomes. We combine Product Development, Artificial Intelligence, and Team Augmentation to craft digital products and solutions that create lasting impact — guided by a human-centric approach and a commitment to pushing the boundaries of what technology can do.

We are looking for a Senior Machine Learning Engineer to own LLM-powered systems end-to-end - from a first proof of concept built in days, to a production system a client trusts with their core workflows. You will work inside AI Labs, where most engagements start as an ambiguous business problem (complex legal documents, scanned and digital; extraction, classification, assistants, agents) and end as a working system with measurable quality.

This is a hybrid of engineer and scientist. You write production-grade Python and ship it through CI/CD, and you treat model quality as an engineering discipline: you do not say "it works" — you show the eval. Curated datasets, graded criteria, baselines, regression thresholds wired into CI. You know that an LLM feature without evals is an untested feature, and you build the measurement before you build the demo.

You are vendor-agnostic and cost-aware: you choose between a prompt, a RAG pipeline, a fine-tune, a classical model, or plain deterministic code based on the problem, the latency budget, and the cost per request - not on what is fashionable. You use AI tools daily to accelerate your own work, with the judgment to know when to trust the output and when not to.

Because we are a consultancy, you are also client-facing: you demo live, explain trade-offs to non-technical stakeholders, size effort honestly in pre-sales, and turn what you learn into assets the rest of the company can reuse. This is not a role for someone who waits for a well-specified ticket. We need an engineer who challenges the framing of the problem, says when the data does not support the ask, and treats production confidence as a deliverable.

Required Qualifications

• 5+ years of professional software engineering experience, with production ownership — not notebooks handed off to someone else.
• 2+ years building LLM-powered systems in production or in delivered client engagements: prompt engineering, structured extraction, RAG, workflows, or agents.
• Experience designing and running evals: building eval datasets, defining graded criteria, establishing baselines and regression thresholds, and using them as a release gate. Candidates who have only eyeballed outputs will not pass this bar.
• Advanced Python: clean, tested, reviewable code; async, typing, packaging, dependency management.
• Hands-on MCP experience and judgment on when to expose capability as a tool/server rather than hard-wire it.
• Hands-on RAG experience: chunking, embeddings, vector stores, reranking and the ability to explain how retrieval quality was measured.
• Experience with at least one LLM orchestration framework (LangChain/LangGraph, LlamaIndex, Pydantic AI, or equivalent) and the judgment to work without one.
• Cloud deployment of AI/ML workloads, preferably AWS (Bedrock, SageMaker, Lambda, ECS, S3) or demonstrable equivalent on GCP/Azure.
• CI/CD and engineering hygiene: Git, automated tests, reproducible builds, containerization; ability to ship without a platform team holding your hand.
• Practical understanding of cost and latency engineering for LLM systems: token accounting, caching, model routing, streaming.
• Awareness of LLM security and privacy risks: prompt injection, data leakage, PII handling in a client-data context.
• AI-first working style: daily hands-on use of AI coding tools (Claude Code, Cursor, Copilot, or similar) with the judgment to know when to trust the output.
• Senior judgment: operate autonomously, challenge an ill-posed problem, prioritize by risk and business impact, own outcomes.
• Excellent written and spoken English; comfortable in a fully remote, distributed, client-facing team.

Preferrable:

• - Experience with an eval or LLM-observability framework (LangSmith, Langfuse, Weave, Braintrust, Arize Phoenix, DeepEval, Ragas, or similar).
• - Experience building LLM-as-judge graders and validating judge/human agreement.
• - Fine-tuning / adaptation experience (LoRA, SFT, distillation) and a clear view of when it pays off versus prompting or RAG.
• - Hands-on deep learning: PyTorch, with models trained on real projects.
• - Classical ML and NLP depth: classification, NER, embeddings, recommendation, time series.
• - MLOps tooling: MLflow, Weights & Biases, DVC, model/prompt versioning and registries.
• - Serving open-weight models (vLLM, Ollama, Bedrock/SageMaker endpoints) and reasoning about GPU cost.
• - Voice / real-time interfaces (STT, TTS, streaming agents).
• - Legal, financial, or other regulated-domain document experience.
• - Consulting or client-facing delivery experience; live demos, discovery, pre-sales.
• - Public evidence of craft: open-source contributions, papers, talks, or a track record of writing about applied AI.

Benefits

• Monthly USD Service Fee
• 20 business days of paid Agreed Time Off—Annual + 6 Local Holidays
• Caregiver Time Off
• A dynamic remote work culture. You can work from anywhere!
• An entrepreneurial environment.

About us

In 2010, our founders dreamed up a company that could positively impact the world. Since then, we've been in permanent evolution: from business consulting to innovation and design, and now to building amazing digital products powered by AI. We scaled globally, launched AI Labs and Reshape Studios, and claimed our space as an AI consulting firm — helping organizations move from pilots to production through accountable AI. Today, we're expanding our impact across industries, driving real AI adoption through accountability, governance, and value at scale. Dreamers first, builders always.

Please note that the role is 100% in English on a daily basis.