Job Description
Job Description
We are seeking a Machine Learning Engineer to join our team. Based in Chicago, Illinois, this role is in the IT industry and provides an opportunity to work on cutting-edge technologies.
As a Software Engineer III, you will be responsible for developing and maintaining machine learning models and systems. This role offers a long-term contract employment opportunity.
Responsibilities :
- Develop and implement machine learning models such as XGBoost, Random forest, KNN, Time series forecasting, regression, classification
- Work with Python and its popular libraries for machine learning and data processing
- Utilize SQL for database management and data manipulation tasks
- Implement Neural Network Architectures, Transformers, ANN, BERT, GPT models, Open Source foundational models
- Utilize cloud-based ML managed services, experience with Azure is valued
- Work with Vector databases, LM / LLM / GEN-AI based tools, libraries and frameworks
- Evaluate performance of ML / DL / LLM systems, handle drift, and use evaluation and explainability frameworks
- Handle end-to-end ML project lifecycle workflows and adhere to MLOps / LLMOps best practices
- Maintain clear communication and presentation skills to work effectively within a team
- Ensure production quality and adherence to best practices in software engineering.
Experience : 3-5years
Education : Masters(preferred) / Bachelors in Computer Science, Mathematics, Statistics, Engineering, In formation Technology or related
Core Skills :
1. Python along with popular and widely used Python libraries
2. SQL
3. ML models like XGBoost, Random forest, KNN, Time series forecasting, regression, classification
4. Neural Network Architectures, Transformers, ANN, BERT, GPT models, Open Source foundational models(e.g; LLama2 / 3, Hugging Face).
5. mlFlow
6. Cloud(Azure is valued over AWS / GCP) based ML managed services(e.g; Azure OpenAI, Azure ML).
7. Vector databases, LM / LLM / GEN-AI based tools, libraries and frameworks(e.g; LangChain, Semantic Kernel).
8. Performance evaluation of ML / DL / LLM systems, drift handling, evaluation frameworks, explainability frameworks
9. End to end ML project lifecycle workflows, experience working with MLOps / LLMOps best practices
Experience with PySpark / Databricks is valued, not mandatory.
Non Technical skills : Great Team player with excellent communication and presentation skills. Self motivated.
Experience of taking ML and / or LLM based systems or DL / Neural Network based systems or mixture of experts based systems to production, is highly valued.
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