Machine Learning AI Data Scientist

Overview

Hybrid
Depends on Experience
Accepts corp to corp applications
Contract - Independent
Contract - W2
Contract - 1 Year(s)

Skills

ML
AI
CNNs
RNNs
LLMs
diffusion models
ensorFlow
PyTorch
AWS
GCP
Azure

Job Details

Client is looking for Data Scientist / Machine Learning Engineer to join our growing AI and ML team. This role is perfect for someone passionate about cutting-edge machine learning technologies, with deep expertise in Data Science, Deep Learning, and Generative AI. You will play a key role in designing and deploying intelligent systems that drive strategic decisions and user-centric innovations across the organization.

Key Responsibilities

  • design, development, and deployment of machine learning and generative AI models.
  • Collaborate cross-functionally with data engineers, product teams, and business stakeholders to identify high-impact AI use cases.
  • Build and refine deep learning architectures (e.g., CNNs, RNNs, Transformers) for complex tasks including NLP, CV, and time series analysis.
  • Develop and manage data pipelines and training workflows for scalable model deployment.
  • Monitor and evaluate model performance using advanced statistical methods and iterate accordingly.
  • Drive experimentation with emerging technologies in generative AI (e.g., LLMs, diffusion models).
  • Mentor junior data scientists and machine learning engineers within the team.
  • Advocate for best practices in ML Ops, data governance, and responsible AI.

Required Qualifications

  • Bachelor s or master s degree in computer science, Data Science, Statistics, or related field (PhD preferred).
  • 5+ years of experience in Machine Learning and Data Science, with at least 2 years in a lead or senior role.
  • Hands-on experience with deep learning frameworks such as TensorFlow, PyTorch, Keras, or Hugging Face.
  • Strong experience with large-scale data processing tools (e.g., Spark, Dask, Airflow).
  • Proven expertise in generative AI technologies (e.g., GPT, Stable Diffusion, VAEs).
  • Proficiency in Python and ML libraries (e.g., scikit-learn, XGBoost, pandas).
  • Solid understanding of software engineering principles and experience with cloud platforms (AWS, Google Cloud Platform, Azure).
  • Excellent communication and collaboration skills.
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About Cyma Systems Inc