
Artificial Intelligence Machine Learning Engineer (Remote)
Hire Feed · United States
- Hybrid
- Contract
- $130,000 / year
- United States
Job highlights
- Develop AI/ML models for global organizations.
- Leverage domain expertise to train AI.
- Collaborate with cross-functional teams.
- Implement and optimize data pipelines.
- Work remotely on cutting-edge AI projects.
About the role
Artificial Intelligence Machine Learning Engineer (Remote)
We are hiring for one of our clients, seeking an AI/ML Engineer to work on a contractor basis. In this role, you will contribute to the development of next-generation AI systems by leveraging domain expertise to shape how models learn, reason, and perform through high-quality, real-world input. This is a unique opportunity to apply your skills in a dynamic environment that bridges human expertise with advanced AI technologies across domains such as finance, healthcare, and engineering. Your work will directly impact the performance and reliability of AI models used by leading organizations globally.
Key Responsibilities:
- Design, develop, and deploy machine learning models to address complex business and technical challenges in alignment with AI system requirements.
- Collaborate with cross-functional teams to translate domain-specific expertise into structured training data, evaluations, and feedback loops that enhance AI model performance.
- Implement, optimize, and maintain ETL processes to ensure efficient data ingestion, transformation, and management for AI model training.
- Utilize Python and relevant libraries to create clean, efficient, and reusable code for machine learning applications and data pipelines.
- Continuously monitor, evaluate, and improve the accuracy and performance of deployed AI models through rigorous testing and iterative refinement.
Required Skills & Qualifications:
- Proficiency in Python and familiarity with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch, with experience in model development and deployment.
- Strong understanding of ETL processes, data pipelines, and tools for data ingestion, transformation, and management in AI applications.
- Experience in developing and optimizing machine learning models, including feature engineering, model training, and evaluation.
- Ability to collaborate effectively with technical and non-technical stakeholders to translate domain knowledge into actionable AI inputs.
- Familiarity with data quality assessment, performance monitoring, and iterative improvement of AI models in production environments.
More About the Opportunity:
This role offers a distinctive opportunity to work within a global network of experts contributing to the human intelligence layer for AI. You will engage with cutting-edge reinforcement learning environments and advanced evaluation frameworks, enabling you to directly influence how AI systems evolve. The platform’s AI-powered recruitment system ensures a high-quality, scalable workflow, providing exposure to projects with high societal and industry impact.
Equal Opportunity Employer:
We hire based on skills and expertise. All qualified candidates are welcome regardless of background, experience, or prior employment history. Applications are reviewed solely on demonstrated technical ability and qualifications.
Key skills/competency:
- Machine Learning
- Python
- Data Pipelines
- Model Deployment
- ETL Processes
- Feature Engineering
- AI Systems
- Data Transformation
- Model Evaluation
- Reinforcement Learning
Skills & topics
- AI Engineer
- Machine Learning Engineer
- Python
- TensorFlow
- PyTorch
- scikit-learn
- ETL
- Data Pipelines
- Model Deployment
- Remote
How to get hired
- Tailor your resume: Highlight Python, ML libraries (scikit-learn, TensorFlow, PyTorch), and ETL experience relevant to AI/ML.
- Showcase collaboration: Emphasize your ability to translate domain knowledge into AI inputs for cross-functional teams.
- Demonstrate technical skills: Clearly outline your experience in model development, deployment, and performance monitoring.
- Prepare for technical interviews: Be ready to discuss ML concepts, Python coding, and data pipeline design for AI systems.
- Express interest in impact: Communicate your passion for contributing to AI with societal and industry significance.
Technical preparation
Behavioral questions
Frequently asked questions
- What specific Python libraries are most important for this AI Machine Learning Engineer role at Hire Feed?
- Proficiency in Python is essential, along with experience in machine learning libraries such as scikit-learn, TensorFlow, or PyTorch. Highlighting your practical application of these libraries in model development and deployment will strengthen your application for this AI Machine Learning Engineer position.
- How does the AI Machine Learning Engineer role at Hire Feed contribute to AI model performance?
- As an AI Machine Learning Engineer, you will leverage domain expertise to shape how AI models learn and perform. This involves contributing high-quality, real-world input through structured training data, evaluations, and feedback loops, directly impacting model reliability and accuracy.
- What is the expected work arrangement for the AI Machine Learning Engineer position?
- This AI Machine Learning Engineer role is fully remote, offering the flexibility to work from anywhere. This allows for a global collaboration with experts contributing to the human intelligence layer for AI.
- What kind of data management experience is crucial for an AI Machine Learning Engineer at Hire Feed?
- A strong understanding of ETL processes, data pipelines, and tools for data ingestion, transformation, and management is crucial. This ensures efficient data handling for AI model training and supports the continuous monitoring and improvement of AI models in production.
- How does Hire Feed ensure a fair application process for the AI Machine Learning Engineer role?
- Hire Feed is committed to an equal opportunity employer policy. Applications for the AI Machine Learning Engineer role are reviewed solely based on demonstrated technical ability and qualifications, irrespective of background or prior employment history.