United States onlyThis position is posted by Jobgether on behalf of a partner company. We are currently looking for an Application Developer - Cognitive Application Automation in United States.
This role offers a unique opportunity to design, build, and automate cutting-edge machine learning workflows and pipelines in a cloud-first environment. You will work with advanced tools and technologies to deploy and manage LLM or RAG-based models, ensuring scalable, secure, and cost-efficient solutions. Collaborating closely with cross-functional teams, you will implement CI/CD pipelines, containerization, and orchestration strategies to optimize ML environments. This position provides exposure to the full lifecycle of machine learning operations, from development to production, while contributing to high-impact automation projects in a remote and fast-paced setting.
Accountabilities:
- Design, implement, and automate ML workflows and pipelines using AWS SageMaker, Lambda, Step Functions, ECS/EKS, and S3.
- Deploy, manage, and monitor LLM or RAG-based models using SageMaker JumpStart or custom endpoints.
- Implement CI/CD pipelines, containerization strategies, and orchestration frameworks for ML environments.
- Ensure solutions are scalable, secure, cost-efficient, and aligned with AWS best practices.
- Collaborate with teams to implement monitoring frameworks and manage feature stores/data versioning.
- Troubleshoot, optimize, and maintain ML environments to ensure reliability and performance.
- Document workflows, processes, and technical solutions to support reproducibility and team knowledge sharing.
Requirements
- 10+ years of experience in Software Engineering, DevOps, or Data Platform Engineering, with at least 5+ years in MLOps.
- Strong expertise in AWS services: SageMaker Studio, Pipelines, Model Registry, Experiments, Model Monitor, Lambda, Step Functions, ECS/EKS, S3, Glue, CloudWatch, CodePipeline.
- Proficiency in Terraform or CloudFormation for Infrastructure as Code.
- Advanced Python, Bash, and Boto3 scripting skills.
- Experience with CI/CD, Docker, Kubernetes/EKS, and container orchestration.
- Hands-on experience deploying LLM or RAG models, managing feature stores, and implementing monitoring frameworks such as Prometheus, Grafana, or EvidentlyAI.
- AWS certifications preferred.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
- Excellent verbal and written communication skills, with the ability to interact professionally with diverse teams.
Benefits
- Competitive hourly rate: $50.00 – $120.00/hour, based on experience and location.
- Remote work opportunity.
- Exposure to advanced ML and cloud technologies in high-impact projects.
- Hands-on experience with end-to-end ML pipeline development and deployment.
- Opportunity to grow technical expertise in cloud computing, MLOps, and AI applications.
- Collaboration with cross-functional teams on cutting-edge automation solutions.
Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.
When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly:
- 🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.
- 📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.
- 🎯 Based on this analysis, the top 3 candidates with the highest match are automatically shortlisted.
- 🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.
The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once shortlisted, your profile is shared with the hiring company, who will manage interviews and next steps.
