Hiring: W2 Candidates Only
Visa: Open to any visa type with valid work authorization in the USA
Job Description:
We are seeking a Machine Learning Engineer to design build and deploy machine learning solutions that support high-impact business initiatives. You will collaborate with data engineers data scientists and software teams to implement end-to-end ML pipelines optimize model performance and deliver production-ready solutions.
This role requires strong knowledge of ML algorithms data preprocessing model lifecycle management and cloud-based ML platforms.
Responsibilities:
Develop train and optimize machine learning and deep learning models
Build automated ML pipelines for data ingestion training validation and deployment
Deploy models into production using ML Ops best practices
Monitor model performance retrain models and improve accuracy and reliability
Work with data engineering teams to ensure high-quality well-structured datasets
Perform feature engineering hyperparameter tuning and model evaluation
Document modeling approaches assumptions outcomes and technical details
Collaborate with software engineers to integrate ML into enterprise applications
Required Skills:
4-10 years of machine learning engineering experience
Strong Python programming skills (NumPy Pandas Sci-Kit Learn)
Experience with TensorFlow PyTorch or Keras
Strong SQL and data manipulation skills
ML Ops tools: Kubeflow MLflow SageMaker or Vertex AI
Experience with cloud platforms (AWS/GCP/Azure)
Understanding of distributed computing and GPU-based processing
Hiring: W2 Candidates OnlyVisa: Open to any visa type with valid work authorization in the USA Job Description:We are seeking a Machine Learning Engineer to design build and deploy machine learning solutions that support high-impact business initiatives. You will collaborate with data engineers data...
Hiring: W2 Candidates Only
Visa: Open to any visa type with valid work authorization in the USA
Job Description:
We are seeking a Machine Learning Engineer to design build and deploy machine learning solutions that support high-impact business initiatives. You will collaborate with data engineers data scientists and software teams to implement end-to-end ML pipelines optimize model performance and deliver production-ready solutions.
This role requires strong knowledge of ML algorithms data preprocessing model lifecycle management and cloud-based ML platforms.
Responsibilities:
Develop train and optimize machine learning and deep learning models
Build automated ML pipelines for data ingestion training validation and deployment
Deploy models into production using ML Ops best practices
Monitor model performance retrain models and improve accuracy and reliability
Work with data engineering teams to ensure high-quality well-structured datasets
Perform feature engineering hyperparameter tuning and model evaluation
Document modeling approaches assumptions outcomes and technical details
Collaborate with software engineers to integrate ML into enterprise applications
Required Skills:
4-10 years of machine learning engineering experience
Strong Python programming skills (NumPy Pandas Sci-Kit Learn)
Experience with TensorFlow PyTorch or Keras
Strong SQL and data manipulation skills
ML Ops tools: Kubeflow MLflow SageMaker or Vertex AI
Experience with cloud platforms (AWS/GCP/Azure)
Understanding of distributed computing and GPU-based processing
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