BayOne Solutions

Machine Learning Engineer(LLM/Python)

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning Engineer (LLM/Python) in San Jose, CA, hybrid (3 days onsite/week), for 6-12 months at $60-70/hr. Requires strong Python skills, hands-on LLM experience, and knowledge of PyTorch and distributed training frameworks.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
560
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πŸ—“οΈ - Date
January 9, 2026
πŸ•’ - Duration
More than 6 months
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🏝️ - Location
Hybrid
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πŸ“„ - Contract
W2 Contractor
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
San Jose, CA
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🧠 - Skills detailed
#SageMaker #AWS SageMaker #AI (Artificial Intelligence) #Computer Science #Model Deployment #PyTorch #Security #Databases #AWS (Amazon Web Services) #Deployment #Hugging Face #MLflow #Java #Compliance #Cloud #Python #GCP (Google Cloud Platform) #Azure #ML (Machine Learning) #FastAPI #C++ #Data Pipeline #Programming #"ETL (Extract #Transform #Load)"
Role description
Position: Machine Learning Engineer Location: San Jose, CA (Hybrid - 3 Days Onsite/Week). Duration: 6-12 Months (Possible Extension or FTE conversion) Pay Rate: $60-70/hr on W2 About Position: We are seeking a hands-on Machine Learning Engineer with a strong computer science foundation and practical experience building LLMs. This role is 100% technical and requires an engineer who can design, train, optimize, and deploy LLMs for real-world applications. Responsibilities β€’ Design, train, and fine-tune specific LLMs for enterprise use cases. β€’ Build robust data pipelines for large-scale text preprocessing and model training. β€’ Optimize LLMs for efficiency using techniques such as LoRA, quantization, and distributed training. β€’ Deploy and serve models in production environments using modern ML infrastructure. β€’ Collaborate with the AI Innovation core team to research, test, and scale new LLM architectures and techniques. β€’ Work closely with cross-functional teams to apply models to security assessment and future CX use cases. Must-Have Qualifications β€’ Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field. β€’ Strong programming skills in Python (with C++/Java as a plus). β€’ Hands-on experience building and training LLMs (small, medium, or large scale). β€’ Deep understanding of transformer architectures, tokenization, embeddings, and pretraining vs. fine-tuning methods. β€’ Proficiency with PyTorch (primary) and familiarity with Hugging Face ecosystem. β€’ Experience with distributed training frameworks (DeepSpeed, FSDP, DDP, Accelerate, Horovod). β€’ Knowledge of model deployment tools (ONNX, TorchScript, Triton Inference Server, FastAPI). Good-to-Have Skills β€’ Familiarity with MLOps workflows (MLflow, Weights & Biases, ClearML). β€’ Knowledge of vector databases (FAISS, Pinecone, Weaviate, Milvus) and RAG pipelines. β€’ Experience with cloud ML platforms (AWS SageMaker, Azure ML, GCP Vertex AI). β€’ Background in security/compliance-aware ML (prompt injection defense, data leakage prevention). β€’ Collaboration and communication skills to work with local and global teams. BayOne is an Equal Opportunity Employer and does not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any federal, state, or local protected class. This job posting represents the general duties and requirements necessary to perform this position and is not an exhaustive statement of all responsibilities, duties, and skills required. Management reserves the right to revise or alter this job description.