AI/ML engineer resume template (ATS-friendly)

A machine learning engineer resume with 5 years of experience covering generative AI (LLMs and RAG), classic NLP and MLOps, with every claim backed by accuracy, latency or cost numbers. Swap in your own models, stack and results.

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What this template includes

GenAI work (RAG, evaluation, fine-tuning) described with measurable outcomes
Model quality paired with production metrics: latency, cost and throughput
Skills split into ML and GenAI, MLOps, and data and cloud for keyword matching
Open-source project with real usage signals

Sample ai/ml engineer resume

Vikram Reddy

AI/ML Engineer · LLMs, RAG & MLOps

Summary

Machine learning engineer with 5 years of experience taking NLP and generative AI models from prototype to production. Builds RAG pipelines, evaluation suites and MLOps tooling that keep LLM features accurate, fast and affordable at scale.

Experience

Senior ML Engineer, Clearpath Insurance Tech (Apr 2023 – Present)

Built a RAG-based claims assistant on 400K policy documents using LangChain and pgvector, cutting agent lookup time by 45%
Created an LLM evaluation suite of 1,200 labelled questions, raising answer accuracy from 71% to 89% before launch
Reduced LLM inference cost by 38% through prompt caching, model routing and a fine-tuned 8B open-source model
Set up MLflow and Kubernetes pipelines that cut model deployment time from 2 weeks to 2 days

Machine Learning Engineer, Tatva Fintech (Jun 2021 – Mar 2023)

Trained a BERT document classifier for KYC forms at 94% accuracy, automating 60% of manual reviews
Served models with FastAPI and Docker at 300 requests per second with p95 latency under 120 ms
Built drift monitoring with Evidently that flagged 3 data issues before they reached customers

Skills

ML & GenAI: PyTorch, Hugging Face Transformers, LLMs, RAG, LangChain, fine-tuning (LoRA), prompt engineering, NLP
MLOps: MLflow, Docker, Kubernetes, FastAPI, Airflow, model monitoring
Data & cloud: Python, SQL, pgvector, Pinecone, AWS (SageMaker, Bedrock), GCP Vertex AI

Projects

IndicQA

Fine-tuned a small open model for Telugu and Hindi question answering; 900+ GitHub stars and 15K Hugging Face downloads

Education

B.Tech, Computer Science, IIIT Hyderabad (2017 – 2021)

CGPA 8.8/10

Certifications

AWS Certified Machine Learning – Specialty (2024)

Top skills for AI and machine learning engineers

Python
PyTorch
Hugging Face Transformers
LLMs
RAG
LangChain
Vector databases
Fine-tuning (LoRA)
LLM evaluation
MLOps
MLflow
Docker
Kubernetes
AWS SageMaker

AI/ML Engineer resume summary examples

Computer science graduate with internship experience in NLP and LLM applications. Built a RAG chatbot and fine-tuned a small transformer model in college projects, and looking for an entry-level machine learning engineer role.

ML engineer with 4 years of experience shipping NLP and recommendation models to production. Strong in PyTorch, FastAPI and MLflow, with a focus on reliable pipelines, monitoring and low-latency serving.

Backend engineer moving into AI engineering after 6 years of building APIs in Python. Has built and deployed 2 LLM-powered features with RAG and evaluation suites, combining software engineering discipline with applied ML.

AI/ML Engineer resume bullet point examples

Built a hybrid search pipeline (BM25 plus embeddings) that raised retrieval recall@5 from 0.62 to 0.81 on 2M support articles
Fine-tuned a 7B open model with LoRA on 30K labelled tickets, matching a larger hosted model at 60% lower cost
Added guardrails and automated LLM evals to CI, catching 25 regressions before release over 6 months
Cut GPU training costs by 30% by moving to spot instances and mixed-precision training on AWS
Deployed a fraud detection model scoring 5K transactions per second with p99 latency under 50 ms

Frequently asked questions

What should an AI/ML engineer resume include in 2026?

Production work first: models or LLM features you shipped, how you evaluated them and what they changed. Name the stack (PyTorch, Hugging Face, LangChain, MLflow, a cloud platform) and show you can handle data, serving and monitoring, not just training.

How do I show LLM and RAG experience on a resume?

Describe the system, the data size and a measured result, for example retrieval recall, answer accuracy on an evaluation set, latency or cost per query. Avoid vague lines like "worked with ChatGPT".

Do I need a master’s degree for machine learning engineer roles?

Not always. Many teams in India hire B.Tech graduates with strong projects, internships or open-source work. Research-heavy roles are more likely to ask for an M.Tech, MS or PhD.

Should I list Kaggle competitions?

List a strong finish (for example a top 5% medal) under Achievements or Projects. Hiring managers usually weigh deployed, end-to-end projects more than leaderboard scores.

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