Overview
Skills
Job Details
Position Title: AI/ML Engineer
Location: Dallas, TX & NYC/Jersey City, NJ - Onsite
Type of Hire: Full-Time Employee (FTE) / Direct W2
Visa: Independent only (No sponsorship)
Who We Are Looking For
We are seeking a seasoned AI/ML Engineer with 12+ years of experience in designing and deploying machine learning systems. The ideal candidate will have expertise in MLOps, cloud-native tools, and the end-to-end ML lifecycle, with a passion for solving complex problems through automation, performance optimization, and scalable architecture.
Key Responsibilities
- Automate model deployment, monitoring, and retraining workflows.
- Build and deploy ML training/inference tools tailored to business use cases.
- Design MLOps pipelines and drive alignment with industry best practices.
- Manage system-wide issues including data drift, model drift, and performance bottlenecks.
- Leverage cloud infrastructure (AWS/Azure/Google Cloud Platform) for scalable model deployment.
- Evaluate emerging technologies to boost scalability and reliability.
- Collaborate with cross-functional teams (data scientists, architects, PMs).
- Present technical designs, documentation, and research contributions to stakeholders.
Technical Skill Matrix
Skill Area | Skill/Technology | Proficiency Required |
Languages | Python | Must Have |
Java, C#, or JavaScript | Good to Have | |
ML Frameworks | TensorFlow, PyTorch, Scikit-learn | Must Have |
MLOps Tools | MLflow, Kubeflow | Must Have |
Cloud Platforms | AWS, Azure, Google Cloud Platform | Must Have |
Containerization | Docker, Kubernetes | Must Have |
Data Engineering | Data architecture, ETL processes, pipeline optimization | Must Have |
ML Engineering | Model versioning, data/model drift detection | Must Have |
API Development | Backend APIs in Python using FastAPI, Flask, Django, etc. | Must Have |
Development Practices | SDLC, Agile/Scrum, test automation | Must Have |
Process Skills
- Agile & Scrum methodology experience
- Requirement gathering and technical documentation
- Exposure to DevOps/MLOps collaboration workflows
Behavioral Skills
- Collaborative team player with cross-functional communication skills
- Strong problem-solving mindset
- Ability to translate technical findings to non-technical audiences
- Open to feedback and eager to learn new technologies
- Demonstrates ownership and independent initiative
- Quick learner with a passion for AI and cloud innovation
Preferred Qualifications
- Bachelor s or Master s in Computer Science, AI/ML, or related field
- Portfolio showcasing real-world AI/ML/NLP implementations
Certifications (Good to Have)
- AWS/Google Cloud Platform/Azure Cloud Certifications
- AI/ML or Data Science Certifications