Senior Machine Learning Engineer - Hybrid
USA, Massachusetts, Boston, 200 Berkeley Street, United States
R
USD 107K-199K Senior-level Full Time
Tasks
- Automate workflows
- Build RAG applications
- Conduct prompt engineering
- Deploy machine learning models to production
- Design implement MLOps platforms
- Design scalable machine learning pipelines
- Evaluate optimize machine learning models
- Fine-tune LLM models
- Integrate machine learning models into existing systems
- Manage data science infrastructure
- Mentor associates on MLOps best practices
- Monitor model performance
- Operationalize analytics solutions
- Package machine learning models
- Propose implementation tools
- Stay current on machine learning and MLOps techniques
- Support generative AI development
Perks/Benefits
- Employee assistance program
- Health, dental, vision insurance
- Hybrid work schedule
- Life insurance
- Long-term disability
- Paid time off
- Retirement savings plan
- Short-term disability
- Wellness benefits
Skills/Tech-stack
API | AWS | Agile | Apache Spark | Azure | BERT | Cassandra | Cloud Computing | Databricks | Docker | EMR | ETL | Elasticsearch | Feature Engineering | Fine Tuning | GCP | GPT | Hadoop | Kanban | Keras | Kubernetes | Language Models | Large Language Models | Linux | Llama | Microservices | MongoDB | MySQL | OCR | Open Source | Open Source Frameworks | OpenCV | Oracle | PostgreSQL | Prompt engineering | PySpark | PyTorch | Python | RAG | Redis | SAFe | Scikit-learn | Scrum | Spark SQL | T5 | TensorFlow | Tesseract | Transformers | XGBoost
Education
Regions
Countries
States
Cities
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