Mindlance

AI/ML Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI/ML Engineer in Washington, DC, for 5 months at a hybrid work setup. Key requirements include 8 years of IT experience, 3-4 years in AI/ML, proficiency in Python and ML frameworks, and cloud platform experience.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
544
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πŸ—“οΈ - Date
November 5, 2025
πŸ•’ - Duration
3 to 6 months
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🏝️ - Location
Hybrid
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πŸ“„ - Contract
Unknown
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
Washington DC-Baltimore Area
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🧠 - Skills detailed
#AWS (Amazon Web Services) #Docker #Datasets #ML (Machine Learning) #GCP (Google Cloud Platform) #AI (Artificial Intelligence) #Generative Models #Model Optimization #Scala #Azure #Kubernetes #Python #TensorFlow #Deployment #Cloud #PyTorch #Monitoring
Role description
Role: AI/ML Engineer (Need Local or DMV) Location: Washington, DC Duration: 5 Months Work Setup: Hybrid (4 days onsite per week from Day 1) Job Description: We are seeking a skilled AI/ML Engineer to design, develop, and deploy machine learning models and AI-driven solutions. The ideal candidate will work with large datasets, build predictive and generative models, and integrate them into scalable production applications. Responsibilities: β€’ Minimum 8 years of overall IT experience, including 3-4 years of hands-on AI/ML development experience. β€’ Design, develop, and deploy machine learning and AI models for real-world use cases. β€’ Work with large datasets for data preprocessing, feature engineering, and model optimization. β€’ Demonstrate strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, and scikit-learn. β€’ Develop and fine-tune Large Language Models (LLMs) and implement traditional ML algorithms. β€’ Utilize cloud platforms (AWS, GCP, Azure) for model training, deployment, and monitoring. β€’ Apply containerization tools like Docker and Kubernetes for scalable deployment. β€’ Collaborate with cross-functional teams to integrate ML solutions into enterprise systems. β€’ Stay current with emerging AI/ML technologies, including GPT-based agents and generative AI tools.