Machine Learning Engineer

About the company: Avenue Code is the leading software consultancy focused on delivering end-to-end development solutions for digital transformation across every vertical. We’re privately held, profitable, and have been on a solid growth trajectory since day one. We care deeply about our clients, our partners, and our people. We prefer the word ‘partner’ over ‘vendor’, and our investment in professional relationships is a reflection of that philosophy. We pride ourselves on our technical acumen, our collaborative problem-solving ability, and the warm professionalism of our teams. Avenue Code has been believing in and promoting plurality actions for over 10 years, understanding that recognizing differences and fostering a safe environment, employment opportunities, representation, and support are the best ways to promote an increasingly equitable culture. Key Responsibilities - Design, build, and maintain end-to-end MLOps pipelines for data prep, training, validation, packaging, and deployment. - Develop FastAPI microservices for model inference with clear API contracts, versioning, and documentation. - Define and implement deployment strategies on AKS (blue/green, canary, shadow; champion/challenger) using GitOps with Argo CD. - Architect and evolve a self-serve MLOps platform (standards, templates, CLI/scaffolds) enabling repeatable, secure model delivery. - Operationalize scikit-learn and other frameworks (e.g., PyTorch, XGBoost) for low-latency, scalable serving. - Implement CI/CD for ML (test, security scan, build, package,promote) using GitHub Enterprise and related tooling. - Integrate telemetry and observability (logging, metrics, tracing) and establish SLOs for model services. - Monitor model and data drift; automate retraining, evaluation,and safe rollout/rollback workflows. - Collaborate with software engineers to integrate ML services into client applications and shared platforms. - Champion best practices for code quality, reproducibility, and governance (model registry, artifacts, approvals). Required Qualifications - Strong Python engineering skills and production experience building services with FastAPI. - Proven MLOps experience: packaging, serving, scaling, and maintaining models as APIs. - Hands-on CI/CD for ML (GitHub Enterprise or similar),including automated testing and release pipelines. - Containerization and orchestration expertise (Docker,Kubernetes) with production deployments on AKS. - GitOps experience with Argo CD; practical knowledge of deployment strategies (blue/green, canary, rollback). - Solid understanding of RESTful API design, microservices patterns, and API contract governance. - Experience designing or contributing to an MLOps platform (standards, templates, tooling) for repeatable delivery. - Ability to work cross-functionally with data scientists, software, and platform/SRE teams. Preferred Qualifications - Minimum 2+ years related experience - Experience with ML lifecycle tools (MLflow or similar fortracking/registry) and feature stores. - Exposure to Databricks and enterprise data/compute environments. - Cloud experience on Azure (preferred), plus GCP familiarity and managed ML services. - Familiarity with Agile practices; experience with Helm/Kustomize, secrets management, and security scanning. “Avenue Code discloses salary range information based on our commitment to fairness and transparency. We consider a wide range of factors such as internal equity, geographic location, relevant education, qualifications, certifications, experience, skills, seniority, business or organizational needs, and others. At Avenue Code, it is not typical for an individual to be hired at or near the top of the range for their role, and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range for a Platform Engineer is from USD 80k to USD 100k per year." Avenue Code reinforces its commitment to privacy and to all the principles guaranteed by the most accurate global data protection laws, such as GDPR, LGPD, CCPA and CPRA. The Candidate data shared with Avenue Code will be kept confidential and will not be transmitted to disinterested third parties, nor will it be used for purposes other than the application for open positions. As a Consultancy company, Avenue Code may share your information with its clients and other Companies from the CompassUol Group to which Avenue Code’s consultants are allocated to perform its services.