
AI / Machine Learning Engineer (Intelligent Systems & Generative AI)
- On-site, Hybrid
- San Jose, California, United States
- Austin, Texas, United States
- New York, New York, United States
+2 more- $50,000 - $75,000 per year
- Information Technology
Seeking a creative Generative AI (6 months–2 years exp) to design and deploy LLM-driven solutions. Across the U.S. Exciting opportunity to innovate and build real-world AI applications.
Job description
Job Description
We are seeking a motivated AI / Machine Learning Engineer with hands-on experience in Intelligent Systems and Generative AI to join our growing technology team. This role is ideal for early-career professionals eager to work on real-world AI solutions and scalable ML models.
Experience: 6 Months – 2 Years
Employment Type: W2 Only
Work Authorization: US Citizens Only
Location: Open to Relocation Anywhere in the United States
Key Responsibilities
Design, develop, and deploy Machine Learning and AI models for real-world business problems
Work on Generative AI solutions using LLMs, chatbots, recommendation engines, or text/image generation
Build and optimize data pipelines for model training and inference
Collaborate with data scientists, software engineers, and product teams
Perform model evaluation, tuning, and performance optimization
Implement AI solutions using cloud platforms and modern ML frameworks
Document workflows, models, and technical designs
Nice to Have
Experience with NLP, computer vision, or recommendation systems
Knowledge of AWS, Azure, or GCP
Understanding of MLOps, CI/CD pipelines, Docker, or Kubernetes
Experience working with SQL/NoSQL databases
Exposure to prompt engineering and AI fine-tuning techniques
Education
Bachelor’s degree in Computer Science, AI, Data Science, Engineering, or a related field.
Job requirements
Required Skills & Qualifications
6 months to 2 years of experience in AI / Machine Learning (internships included)
Strong programming skills in Python
Hands-on experience with Machine Learning algorithms (supervised & unsupervised learning)
Exposure to Generative AI / LLMs (OpenAI, Hugging Face, LangChain, etc.)
Experience with ML frameworks: TensorFlow, PyTorch, or Scikit-learn
Basic knowledge of data structures, statistics, and linear algebra
Familiarity with REST APIs and model deployment concepts
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