AI Engineer - NY
Photon.com
45k - 160k USD/year
Office
United States
Full Time
6–7 years of experience in AI/ML engineering, data science, or applied machine learning.
Strong programming skills in Python and familiarity with ML frameworks:
TensorFlow, PyTorch, Keras, JAX, Hugging Face
Experience with:
NLP, CV, predictive modeling, or generative AI
Model deployment and serving (TensorFlow Serving, TorchServe, FastAPI, Triton)
Data processing tools (Pandas, NumPy, Spark)
Strong understanding of:
Machine learning fundamentals, deep learning architectures, and statistics
TensorFlow, PyTorch, Keras, JAX, Hugging Face
NLP, CV, predictive modeling, or generative AI
Model deployment and serving (TensorFlow Serving, TorchServe, FastAPI, Triton)
Data processing tools (Pandas, NumPy, Spark)
Machine learning fundamentals, deep learning architectures, and statistics
Cloud platforms: AWS/GCP/Azure
CI/CD, MLOps, versioning tools (MLflow, DVC, Airflow)
Cloud platforms: AWS/GCP/Azure
- CI/CD, MLOps, versioning tools (MLflow, DVC, Airflow)
- Familiarity with distributed training, vector databases (FAISS, Pinecone, Chroma), and GPU acceleration is a plus.
NicetoHave
- Experience with prompt engineering, multi-agent systems, or RAG frameworks.
- Knowledge of LLM fine-tuning (LoRA, QLoRA, PEFT).
- Experience with real-time inference, model optimizers, quantization.
- Certifications in AI/ML or cloud technologies.
- Experience in domain-specific AI (healthcare, fintech, retail, etc.). Compensation, Benefits and Duration
- Minimum Compensation: USD 45,000
- Maximum Compensation: USD 160,000
- Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
- Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full time employees.
- This position is not available for independent contractors
- No applications will be considered if received more than 120 days after the date of this post
