About the Company
Firehorse, a US-based company, is hiring a Senior Python Engineer with strong programming fundamentals and deep AI expertise spanning both traditional machine learning and generative AI / LLMs. We are looking for someone who moves fast, writes clean and well-tested code, and has a genuine understanding of how models work under the hood.
About the Role
Firehorse is seeking a Senior Python Engineer to design, build, and maintain robust Python services and AI-powered features, with a focus on both traditional ML and GenAI/LLM systems, while collaborating closely with clients and stakeholders and upholding engineering best practices.
Responsibilities
- Design, build, and maintain robust Python services, APIs, and data pipelines.
- Develop AI-powered features using both traditional ML models and LLM / GenAI systems.
- Build and evaluate LLM pipelines — prompt engineering, RAG, fine-tuning, and model evaluation.
- Write end-to-end test cases and maintain high automated test coverage.
- Prototype and iterate quickly — ship at a high pace without sacrificing quality.
- Optimize applications for performance, reliability, and scalability.
- Participate in code reviews and uphold engineering best practices.
- Collaborate directly with clients and stakeholders to shape technical solutions.
Qualifications
- 5+ years of professional Python development experience.
- Strong programming and computer science fundamentals — data structures, algorithms, and clean code.
- Strong AI and LLM skills across both traditional ML (e.g., scikit-learn, PyTorch) and GenAI (e.g., Anthropic / OpenAI APIs, agent and RAG frameworks).
- Solid understanding of how models actually work — architectures, training, inference, and evaluation. This is a must.
- Hands-on experience building RAG systems — retrieval pipelines, vector databases, and evaluation. This is a must.
- Experience writing end-to-end and integration tests (e.g., pytest).
- Experience building and consuming REST APIs; fluency with Git workflows.
- High velocity: able to learn fast, deliver fast, and own outcomes independently.
Preferred Skills
- Open-source model deployment experience (e.g., Hugging Face, vLLM, Ollama, GPU inference).
- Cloud experience (AWS) and containerization (Docker / Kubernetes).
Compensation & Benefits
- Compensation through USD remittance.
- Fuel allowance and company-sponsored lunch.
- Double daily salary for approved weekend or public-holiday work.
- Hybrid schedule — 3 days in office, 2 days remote.
- No micromanagement; direct interaction with stakeholders.
PK
