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Efe Akman

@efeakman

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Senior AI/ML engineer and team lead building production LLM, ML, and MLOps systems.

Germany

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What I'm looking for

I’m looking to lead or controbute to distributed teams building production AI/ML + LLM systems—secure, cost-efficient, and reliability-first—turning research into end-to-end MLOps with measurable business impact. Comfortable as both an IC and tech lead in distributed teams.

I’m a Senior AI/ML Engineer and team lead with 7+ years building production ML, LLM, and MLOps systems in finance and SaaS. I focus on shipping secure, measurable, and maintainable pipelines—where model quality, cost, and reliability are engineered together.

At Proxify, I lead a 3-engineer team on an Azure-based, GDPR-compliant voice-to-structured-output platform. I architected and deployed the system integrating gpt-4o-transcribe and gpt-5 across ACR, Web Apps, and Key Vault for 200+ production users, while owning 31 REST endpoints, Celery/Redis async processing, PostgreSQL, and Dockerized CI/CD.

Previously at Turing, I shipped an internal RAG chatbot using Llama 2, sentence-transformers embeddings, FAISS, FastAPI, and Gradio—enabling Q&A over 5,000 company documents and serving 800 queries per week. I also delivered 3,000+ RLHF evaluations at a 98% acceptance rate, and reproduced 40+ research methods as runnable notebooks with a 95% acceptance rate.

Earlier, at TEB-BNP Paribas, my FastAPI-based end-to-end ML pipeline was adopted by 30+ data scientists and deployed 30+ production models, cutting delivery time by over 80%. I improved loan profit by 87% with a six-model ensemble and increased FX spread revenue by 37%, then owned production deployment, monitoring, and ETL optimization on on-prem infrastructure with Docker, Jenkins, Pytest, Pydantic, Airflow, SQL, and ElasticSearch.

Experience

Work history, roles, and key accomplishments

Current

AI/ML Engineer & Team Lead

Current

Proxify

Sep 2025 - Present (8 months)

Architected and deployed a GDPR-compliant Azure voice-to-structured-output SaaS used by 200+ production users. Led 2 backend engineers and 1 DevOps engineer and owned REST APIs, async processing, PostgreSQL, and Azure CI/CD, while cutting SageMaker inference costs by 93% and maintaining accuracy within 1 percentage point.

Azure LLM Transcription (Gpt 4o Transcribe)VLLM REST API Development PostgreSQL

Senior AI/ML Engineer

Turing

Dec 2023 - Sep 2025 (1 year 9 months)

Shipped an internal RAG chatbot with Llama 2 that enabled Q&A over 5,000 company documents and handled 800 queries per week. Delivered 3,000+ RLHF evaluations with a 98% acceptance rate and reproduced 40+ research methods as runnable notebooks with a 95% acceptance rate.

RAG Systems LLaMA 2 Faiss fastAPI Gradio LLM Evaluation

Senior Data Scientist

TEB-BNP Paribas

Mar 2021 - Dec 2023 (2 years 9 months)

Built a FastAPI-based end-to-end ML pipeline app (preprocessing to evaluation) adopted by 30+ data scientists and used to deploy 30+ production models, cutting project delivery time by 80%+. Increased loan profit by 87% using a six-model ensemble and A/B testing, and raised FX spread revenue by 37% via a FastAPI FX pricing service with GMM segmentation.

fastAPI A B Testing Model Evaluation Docker Airflow SQL Elasticsearch

Data Scientist

Ikon Securities Inc.

Jul 2020 - Mar 2021 (8 months)

Improved an auto-hedging algorithm by 19% by introducing Gaussian Mixture-based customer segmentation to classify risk and success profiles and allocate accounts across the broker team.

Customer Segmentation Auto Hedging Analytics Python Data Modeling scikit learn

Data Scientist

Saka Soft

Feb 2019 - Jul 2020 (1 year 5 months)

Developed a housing price regression model with SageMaker (adjusted R² = 0.76) and deployed it via ECR/EC2 using S3 for storage. Automated retraining and inference using API Gateway and AWS Lambda for production-ready model updates.

Sagemaker Regression Modeling AWS Lambda API Gateway EC2 S3