> Djinni
junior
HebronSoftAI Engineer
format:Remotecompany:Outsource
pythonlanggraphlangchainclaude apigeminiopenaiany one ofclaude apivector databasespytorchtensorflowfastapiflaskany one offastapisqldynamodbmongodbmysqlpostgresqlany one ofdynamodb
mlopsci/cdgpuquantizationawsgoogle cloudazure
semantic dedup
Reposted 2× across DOU + Djinni — deduped to one listing.
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> full description
We are looking for an AI Specialist with strong Python skills and hands-on experience working with modern AI frameworks and LLMs. You will work on building, fine-tuning, and deploying machine-learning models into production, as well as developing Python backend services for model serving.
Responsibilities
- Develop and maintain AI/ML solutions using Python.
- Work with LLMs (OpenAI, Anthropic, Google Gemini) and frameworks like LangGraph and LangChain.
- Build and optimize pipelines using Vector Stores.
- Train, fine-tune, and evaluate ML models (image, text, audio, video).
- Work with neural networks, NLP, computer vision or reinforcement learning tasks.
- Create and improve classification models (shot/scene detection, captions, object labeling, attention scoring, etc.).
- Deploy AI/ML models into production environments.
- Develop Python backend (Flask or FastAPI) for serving models.
- Work with databases (SQL and NoSQL) for data storage, preprocessing, and model input pipelines.
Requirements
- >1 year of experience in AI/ML or applied machine learning.
- Strong Python skills.
- Experience with LLM frameworks: LangGraph, LangChain.
- Hands-on experience with LLMs (OpenAI, Anthropic, Gemini).
- Good knowledge of Vector Stores and their application.
- Solid understanding of ML algorithms, architectures, and workflows.
- Experience with ML frameworks: PyTorch, TensorFlow.
- Experience with image/text/audio/video model training and fine-tuning.
- Experience building backend services with Flask or FastAPI.
- Experience working with SQL and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB, DynamoDB, etc.).
Nice to have
- Understanding of MLOps tools and CI/CD for ML.
- Experience with GPUs, model optimization, quantization.
- Familiarity with cloud platforms (AWS / GCP / Azure).