5-7 years of experience in experiment design and execution for LLM performance testing.
Proficiency in deep learning frameworks like PyTorch, TensorFlow, or Keras.
Experience in evaluating and validating AI systems, particularly LLMs.
Hands-on experience with GPU computing for accelerated model training.
Expertise in tuning neural networks on custom datasets for specific applications.
Experience in developing AI/ML models and selecting optimal Python libraries.
Proficient in Python or R and SQL, including advanced querying techniques.
Familiarity with version control systems such as GitHub and Jenkins.
Responsibilities
Design and execute experiments to benchmark LLM performance.
Develop and tune machine learning models tailored to specific use cases.
Evaluate and validate AI systems, focusing on LLMs.
Leverage GPU resources for efficient model training and testing.
Collaborate with teams to select appropriate libraries and preprocessing methods.
Communicate methodological choices and results effectively to stakeholders.
Maintain version control and documentation of model development processes.
Benefits
Flexible work hours and remote work options.
Opportunities for professional development and training.
Access to cutting-edge technology and tools.
Collaborative and innovative work environment.
Health and wellness programs.
Full Job Description
Job Description
Seeking a Machine Learning Engineer With the following skills:
Required Skills
Demonstrated professional or academic experience in experiment design and execution to test the performance of LLMs against a benchmark.
Demonstrated professional or academic experience with deep learning frameworks such as PyTorch, Tensorflow, or Keras.
Demonstrated professional experience or academic experience in testing, evaluating, or validating the performance of AI systems (with a focus on LLM-based systems
Demonstrated experience leveraging GPUs for accelerated computing.
Demonstrated experience tuning neural networks, such as LLMs, on custom data sets and applying results to specific use cases.
Demonstrated professional or academic experience developing models and ensembles in the AI/ML space, including selecting the best Python libraries for a given task, choosing appropriate pre-processing actions, performing analysis, and assessing model performance.
Demonstrated professional or academic experience using Python or R.
Demonstrated professional or academic experience and proficiency with SQL to include using common table expressions, set operations, aggregated functions and nested subqueries.
Demonstrated professional or academic experience with version control systems such as Github and Jenkins.
Desired Skills
Demonstrated professional or academic experience with the HuggingFace Transformers library and hub.
Demonstrated professional or academic experience in the development of benchmarks to measure LLM performance. (KEY EXPERIENCE FOR CUSTOMER)
Demonstrated experience with cloud computing development and architecture.
Demonstrated experience with front-end web development frameworks such as Flask.
Demonstrated experience creating machine learning models that conduct text classification and topic modeling in Python using standard machine learning (SciKit Learn-) or deep learning models.
Demonstrated experience developing applications for semantic search.
Demonstrated professional or academic experience and proficiency with Tableau to produce visualizations and dashboards.
Demonstrated academic or professional experience communicating methodological choices and model results
Demonstrated experience with verification and validation test benches.
Demonstrated experience with Explainable AI (XAI) techniques.
Demonstrated experience with ONNX (Open Neural Net Exchange).
