Role: – Machine Learning Engineer
Bill Rate: $95/hour C2C
Location: Dallas, TX
Duration: 12+ months/ long-term
Interview Criteria: Telephonic + Skype
Direct Client Requirement
Job Details
We are seeking a skilled and passionate Machine Learning Engineer to join our team and help design, build, and optimize scalable ML solutions. The ideal candidate will have deep expertise in the Python ML ecosystem and experience developing and managing robust model training pipelines.
Key Responsibilities:
· Design and implement scalable machine learning models and training workflows using PyTorch or TensorFlow.
· Develop and maintain end-to-end ML pipelines, from data preprocessing to model deployment.
· Leverage the Python ecosystem (NumPy, pandas, scikit-learn, spaCy, NLTK, Hugging Face Transformers) for feature engineering, model development, and evaluation.
· Manage and track machine learning experiments using MLflow, ensuring reproducibility, versioning, and lifecycle management.
· Collaborate with data scientists, software engineers, and product teams to deploy ML models into production environments.
· Continuously optimize models and pipelines for performance, scalability, and accuracy.
Note: If you are interested, please share your updated resume and suggest the best number & time to connect with you. If your resume is shortlisted, one of our IT Recruiter from my team will contact you as soon as possible
Srinivasa Reddy Kandi
Client Delivery Manager
Valiant Technologies LLC
Equal Opportunity Employer:
We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate based on race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law