
Artificial Intelligence Engineer (Remote)
Hire Feed · United States
- Hybrid
- Contract
- $130,000 / year
- United States
Job highlights
- Design and build advanced machine learning models.
- Automate ML pipelines with CI/CD practices.
- Utilize AWS and Kubernetes for infrastructure.
- Collaborate with diverse technical teams.
- Shape AI systems across industries.
About the role
Artificial Intelligence Engineer (Remote)
We are hiring for one of our clients, seeking an AI Engineer to work on a contractor basis. This role focuses on designing, building, and optimizing machine learning models to train next-generation AI systems with real-world input. The work directly shapes how AI models learn, reason, and perform across domains such as finance, healthcare, and engineering. Candidates with domain expertise in any field are encouraged to apply, as no prior AI experience is required.
Key Responsibilities
- Design, build, and optimize robust machine learning models optimized for production environments.
- Implement and automate end-to-end ML pipelines using CI/CD best practices to ensure reliability and efficiency.
- Leverage AWS services for scalable AI infrastructure, model deployment, and data processing workloads.
- Orchestrate containerized workloads using Kubernetes to maintain high availability and seamless scalability of AI systems.
- Collaborate with cross-functional teams including data scientists, engineers, and researchers to translate complex business problems into actionable ML solutions.
- Evaluate, preprocess, and frame real-world data problems for effective machine learning applications.
- Document solution approaches, methodologies, and findings for internal and external stakeholders.
Required Skills & Qualifications
- Experience with machine learning model development and optimization in production settings.
- Proficiency in implementing CI/CD pipelines for ML workflows using tools such as GitHub Actions, Jenkins, or GitLab CI.
- Hands-on experience with AWS services including EC2, S3, Lambda, SageMaker, and related cloud infrastructure.
- Strong working knowledge of Kubernetes for container orchestration, deployment, and scaling of ML workloads.
- Ability to preprocess, evaluate, and structure domain-specific data for machine learning applications.
- Familiarity with Python and relevant ML libraries such as TensorFlow, PyTorch, or scikit-learn is beneficial.
- Excellent documentation skills and ability to communicate technical concepts clearly to non-technical stakeholders.
More About the Opportunity
This role offers the chance to contribute to a global platform that connects domain experts to the development of frontier AI models. You will work on advanced evaluations and reinforcement learning environments that improve AI system performance across multiple industries. The opportunity provides global exposure, impactful work, and collaboration with leading experts in AI and machine learning.
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
- AI Engineering
- AWS
- Kubernetes
- CI/CD
- Data Preprocessing
- Model Optimization
- Python
- TensorFlow
- PyTorch
Skills & topics
- Artificial Intelligence Engineer
- Machine Learning
- AI
- ML Engineer
- AWS
- Kubernetes
- CI/CD
- Data Science
- Python
- Remote
How to get hired
- Tailor your resume: Highlight machine learning, AWS, and Kubernetes experience.
- Showcase CI/CD skills: Emphasize pipeline implementation and automation successes.
- Detail data experience: Demonstrate proficiency in data evaluation and preprocessing.
- Quantify achievements: Use numbers to show impact in previous ML projects.
- Prepare for technical questions: Be ready to discuss ML models and cloud infrastructure.
Technical preparation
Behavioral questions
Frequently asked questions
- What are the primary responsibilities of an AI Engineer at Hire Feed?
- As an AI Engineer, you will design, build, and optimize machine learning models, implement ML pipelines using CI/CD, leverage AWS services, and orchestrate containerized workloads with Kubernetes. You'll also collaborate with teams and preprocess data for AI systems.
- Is prior AI experience mandatory for this AI Engineer role?
- No, prior AI experience is not required. Candidates with domain expertise in any field are encouraged to apply. The focus is on your ability to learn and apply machine learning principles to real-world data.
- What cloud platforms and tools are essential for this AI Engineer position?
- Hands-on experience with AWS services (EC2, S3, Lambda, SageMaker) and Kubernetes for container orchestration is essential. Familiarity with CI/CD tools like GitHub Actions, Jenkins, or GitLab CI is also important.
- What programming languages and ML libraries are relevant for this AI Engineer role?
- Proficiency in Python and relevant ML libraries such as TensorFlow, PyTorch, or scikit-learn is beneficial for this AI Engineer role. These tools are key for model development and optimization.
- Can I work remotely for this Artificial Intelligence Engineer position?
- Yes, this Artificial Intelligence Engineer position is fully remote, allowing you to work from anywhere. This offers flexibility and global exposure.
- What kind of data will I be working with as an AI Engineer?
- You will work with real-world data across various domains like finance, healthcare, and engineering. A key part of the role involves evaluating, preprocessing, and structuring this domain-specific data for machine learning applications.
- What is the expected payout for the Artificial Intelligence Engineer role?
- The expected payout for this Artificial Intelligence Engineer role is between $30 and $130 per hour, based on your experience and qualifications.