Ai/ml Engineer
Build and deploy AI/ML models (LLMs, RAG, NLP, generative AI) on a large-scale platform using Python, TensorFlow, Scikit-learn, and AWS, with full MLOps and data engineering responsibilities.
- Compensation
- Not disclosed
- Location
- Worldwide
- Work setup
- Remote
- Seniority
- Not specified
- Employment
- Contract
- Experience
- Not specified
- Category
- Ml / AI
- Posted
Skills
Must have
- API Development
- AWS
- Advanced Machine Learning
- Cloud Services
- Data Analysis
- Data Modeling
- Data Preprocessing
- Deep Learning
- Feature Engineering
- Model Deployment
- Model Evaluation
- Model Optimization
- Python
- SQL
- Scikit-learn
- TensorFlow
- 8–30 years of experience
Nice to have
- Docker
- Flask
- GCP
- Git
- Keras
- NumPy
- Pandas
- Tableau
Full description
Title: Freelance Ai/ml Engineer
Industry: IT | Work Mode: Remote | Location: Remote
Role Summary
We are seeking a highly skilled Freelance Ai/ml Engineer to contribute to our project titled “AI/ML Engineer (LLM, RAG, Python) - Fulltime, Based-only-US” in the IT industry. This role involves developing a large-scale AI/ML platform that focuses on intelligent automation, predictive analytics, natural language processing (NLP), and generative AI capabilities. You will engage in data engineering, model development, deployment, MLOps implementation, and system optimization while collaborating with AI researchers, data engineers, software developers, and business teams to deliver a scalable, secure, and production-ready solution.
Responsibilities
- Design and implement robust AI/ML models that enhance intelligent automation functionalities and predictive analytics.
- Collaborate closely with cross-functional teams to ensure seamless integration of AI solutions into existing business processes.
- Conduct thorough testing and validation of models to ensure high performance and reliability in production environments.
- Develop and maintain documentation for AI/ML processes, standards, and best practices to facilitate knowledge sharing.
- Stay updated with the latest advancements in AI/ML technologies and methodologies to continuously improve project outcomes.
Ways of Working
- Utilize agile methodologies to manage project timelines and deliverables effectively.
- Foster a culture of open communication and collaboration to enhance team performance and innovation.
- Implement asynchronous work practices to accommodate diverse team schedules and maximize productivity.
Collaboration & Communication
- Regularly engage with stakeholders to align project goals and expectations.
- Provide updates on project progress, challenges, and milestones to ensure transparency and accountability.
- Participate in code reviews and knowledge-sharing sessions to promote continuous learning within the team.
Growth Signals
- Opportunities for professional development through exposure to cutting-edge AI/ML technologies and practices.
- Potential for growth into senior technical roles or leadership positions based on performance and contributions to project success.
- Participation in industry conferences and workshops to enhance skills and expand professional networks.