Ziphire.hr

Compensation

Full Description

About the Role ================== As a Senior Machine Learning Engineer, you will build, deploy, and optimize the machine learning services that power the client's platform. You will be the primary builder of robust ML subsystems, translating high-level requirements into production-ready code. This is a hands-on role where you will focus on the reliability, speed, and scalability of our AI solutions. You will take ownership of specific model pipelines, ensuring they are efficient, testable, and maintainable. Your Area of Focus ====================== Write high-quality, production-grade software for data ingestion, feature extraction, and model inference, specifically focusing on optimizing code for latency, throughput, and resource efficiency. Implement robust CI/CD pipelines, automated testing, and comprehensive logging/monitoring for the models you deploy to ensure immediate detection of issues. Construct and maintain specific data pipelines required for training and inference, ensuring data quality and consistency at the component level. Develop reusable software modules and utilities that streamline the development process for the wider team, while championing clean code and test-driven development. Translate business requirements into technical specifications and execute them with precision, serving as an expert at breaking down complex tasks into deliverable units. Monitor the daily performance of production models, debug incidents, and execute routine retraining workflows to address data drift. Partner with Engineering team members and Product Managers to estimate effort, flag technical risks, and deliver features on schedule. Your Professional Qualifications ==================================== 5+ years of professional software development experience including system design, large-scale services, and production-grade infrastructure. 3+ years of hands-on experience in machine learning engineering or applied AI, with a strong record of deploying and maintaining models in production. Technical subject matter expertise in 3+ general areas of software development (e.g., server, database, security, etc) including machine learning infrastructure. Demonstrated ability to deliver significant, measurable real-world impact through applied ML. Proven ability to design and write modular, performant, and easy to read software that solves complex business problems. Proficiency in Python, TensorFlow/PyTorch, and scikit-learn. Strong background in MLOps and data infrastructure (e.g., Airflow, Spark, feature stores, MLflow, data versioning). Proven ability to deploy and maintain ML models in production with CI/CD, monitoring, and alerting. Familiarity with cloud ML environments (AWS, GCP, or Azure) and containerization (Kubernetes, Docker). Experience building or fine-tuning Large Language Models (LLMs) or generative models for structured business processes. Experience with retrieval-augmented pipelines or feedback-driven model retraining. Excellent technical communication and a product mindset—comfortable driving initiatives from concept to delivery. Bonus Points ================ Background in healthcare software operations, or financial automation. Contributions to open-source ML infrastructure projects. Published research or conference papers in machine learning, natural language processing, or applied AI Experience leading AI reliability and observability initiatives — designing monitoring frameworks, drift detection, and alerting systems for multiple production models. Our Values ============== Start with the Customer --------------------------- We get to know our customers - and their patients - and look at the world through their lens. Keep It Simple ------------------ Healthcare is too complex. We aim to simplify it for everyone. Stay Entrepreneurial ------------------------ We reject the status quo and solve problems with creativity, perseverance, and a bias to action. Better Together ------------------- We are diverse, humble, and collaborative. We put the team first and win together. Celebrate Success --------------------- Life is short and joy is underrated. We take time to have fun and celebrate success. Perks \& Benefits ===================== United States: In addition to our healthcare benefits, we also offer amazing perks! Need work from home basics? We offer a discount through Dell! We also offer a number of resources to help you keep your mind and body healthy. Check out Gympass for a great workout, or TelusEmployee Assistance Program to find mental health resources, along with other resources for everyday occurrences. Costa Rica: To assist with all of life's needs, our client also offers a wellness and childcare subsidy and a University/Education discount! We also offer a number of resources to help you keep your mind and body healthy. Check out Gympass for access to health and fitness apps, or Telus Employee Assistance Program to find mental health resources, along with other resources for everyday occurrences. Compliance \& Privacy Disclosures ===================================== NOTE: Our client is an equal opportunity employer. All applicants will be considered for employment without attention to age, race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status. Key Responsibilities •Build, deploy, and optimize ML services •Write production-grade software for data ingestion •Implement CI/CD pipelines for model deployment •Construct and maintain data pipelines for training •Develop reusable software modules for the team •Translate business requirements into technical specs •Monitor performance of production models •Debug incidents and execute retraining workflows •Collaborate with Engineering and Product Managers •Estimate effort and flag technical risks Qualifications •5+ years of software development experience •3+ years in machine learning engineering •Expertise in 3+ areas of software development •Proven impact through applied ML •Ability to design modular software •Experience with large-scale services •Strong record of deploying models in production •Experience with production-grade infrastructure Training & Development Performance Bonus