Role Description This engagement is focused on building an internal AI platform that enables developers to ship AI-powered services efficiently. The objective is to improve DevEx and reduce time-to-market for AI features. Location: Serbia (relocation support available), Croatia, Poland, Portugal - Build and operate the AI platform infrastructure enabling developers to ship LLM-based services faster. - Implement and maintain Kubernetes-based runtime environments (incl. AKS) for AI workloads. - Manage infrastructure as code with Terraform (modules, environments, CI/CD automation). - Support LLM workflows: RAG, agents, prompt experimentation, evaluations, and deployment patterns. - Integrate and operate tooling such as Azure AI Foundry, LiteLLM, Langfuse, MLflow. - Orchestrate pipelines using Kubeflow Pipelines and/or Argo Workflows (build, deploy, evaluate). - Improve platform reliability and observability (monitoring, logging, tracing, cost/perf signals). - Collaborate closely with developers to streamline DX (APIs, templates, docs, golden paths, automation). Qualifications - Strong hands-on experience with Kubernetes in production (preferably AKS). - Solid Terraform expertise (IaC best practices, multi-env setups). - Practical experience supporting ML/LLM workloads in a platform or DevOps/MLOps context. - Proficiency in Python for automation, scripting, and supporting APIs/evaluation tooling. - Understanding of CI/CD, release processes, and production-grade operations. - Ability to work under tight timelines and deliver pragmatically. Requirements - Experience building internal developer platforms or “paved roads” for engineering teams. - Familiarity with LLM evaluation frameworks, prompt testing workflows, and LLM observability. - Exposure to RAG architectures, vector databases, and agentic patterns. - Experience with Kubeflow, Argo, and ML lifecycle tooling. Benefits - Long-term B2B contract. - Remote work from Croatia, Poland, Portugal, and Serbia. - European working hours. - Occasionally available for meetings up to 10:00 AM PST (US overlap).

ML Engineer Location: 100% Remote (client sits in Dearborn, MI) Employment Type: Contract Job Description: Role Overview We are seeking an AI / ML Engineer to help build and operationalize machine learning capabilities, including model development, deployment, and agent-based systems in a production environment. This role has a heavy MLOps focus where the engineer will help shape and establish practices within a developing MLOps platform. The position is an equal split between ML model development and ML enablement. Key Responsibilities - Build ML models using PyTorch, working with real-time data to solve production problems. - Collaborate with data engineers on data inputs and pipeline construction. - Develop agents in GCP to support the data and ML ecosystem. - Utilize prompt engineering and help operationalize ML workflows. - Deploy ML models into production, understanding concepts like model versioning, monitoring, retraining, and data drift. - Contribute to an evolving environment by helping to define tooling and standards. Required Qualifications Experience: - Proven experience building ML models with PyTorch and deploying them into a production environment. - Familiarity with MLOps concepts and working with real-time data. - Experience with ML deployment and orchestration, preferably with Vertex AI. - Production experience in a core cloud environment, such as GCP. Candidates must have production ML experience. - Comfort working in environments with evolving tooling and standards. Technical Skills: - Python - PyTorch - Vertex AI - GCP Education: - Master's candidates from top programs with hands-on ML experience and exposure to production-level systems are encouraged to apply. Compensation & Benefits The anticipated pay range for this position is $60.00 to $80.00 per hour. Please note that the pay range provided is a good faith estimate for the position at the time of posting. Final compensation may vary based on factors including but not limited to, the candidate's experience, skills, and geographic location. We are an equal opportunity employer and welcome applications from all qualified candidates regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status. Apex uses a virtual recruiter as part of the application process. Click here for more details. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation in using our website for a search or application, please contact our Benefits Department at [email protected] or 804-523-8228. Apex Systems is a world-class IT services company that serves thousands of clients across the globe. When you join Apex, you become part of a team that values innovation, collaboration, and continuous learning. We offer quality career resources, training, certifications, development opportunities, and a comprehensive benefits package. Our commitment to excellence is reflected in many awards, including ClearlyRated's Best of Staffing in Talent Satisfaction in the United States and Great Place to Work in the United Kingdom and Mexico. Apex uses a virtual recruiter as part of the application process. Apex Benefits Overview: Apex offers a range of supplemental benefits, including medical, dental, vision, life, disability, and other insurance plans that offer an optional layer of financial protection. We offer an ESPP (employee stock purchase program) and a 401K program which allows you to contribute typically within 30 days of starting, with a company match after 12 months of tenure. Apex also offers a HSA (Health Savings Account on the HDHP plan), a SupportLinc Employee Assistance Program (EAP) with up to 8 free counseling sessions, a corporate discount savings program and other discounts. In terms of professional development, Apex hosts an on-demand training program, provides access to certification prep and a library of technical and leadership courses/books/seminars once you have 6+ months of tenure, and certification discounts and other perks to associations that include CompTIA and IIBA. Apex has a dedicated customer service team for our Consultants that can address questions around benefits and other resources, as well as a certified Career Coach. You can access a full list of our benefits, programs, support teams and resources within our 'Welcome Packet' as well, which an Apex team member can provide. Employee Type: Contract Remote: Yes Location: Dearborn, MI, US Job Type: Pay Range: $60 - $80 per hour

Role Description We are seeking an E-learning Developer to build interactive online courses and digital learning experiences. You will combine instructional design principles with technical development skills. Key Responsibilities - Develop interactive e-learning modules using authoring tools and HTML5. - Integrate multimedia elements including video, audio, and animations. - Ensure compatibility with LMS platforms (SCORM, xAPI). - Test and quality-assure e-learning content before publication. - Collaborate with instructional designers and subject matter experts. Qualifications - 2+ years of e-learning development experience. - Proficiency in Articulate Storyline, Rise, or similar tools. - Basic HTML/CSS and JavaScript skills for custom interactions. - Experience publishing to LMS platforms. - Strong attention to detail and commitment to learner experience.

Role Description We are seeking a Machine Learning Engineer to develop, train, and deploy ML models that power our core product features. You will bridge the gap between data science research and production-ready systems. Key Responsibilities - Design and implement ML pipelines from data ingestion to model deployment. - Work with data scientists to bring models into production. - Monitor model performance and implement retraining strategies. - Collaborate with backend engineers to integrate ML services. - Stay current with advances in ML research and tooling. Requirements - 3+ years of ML engineering or data science experience. - Proficiency in Python and ML frameworks (TensorFlow, PyTorch, or scikit-learn). - Experience with MLOps tools and cloud ML platforms. - Strong understanding of statistics and model evaluation. - Ability to communicate technical concepts clearly.