Senior Machine Learning Engineer

Hi there, I'm Raùl, Director of Data at TestGorilla. We’re excited to share more about the Senior Software Engineer, AI/ML Platform role and our team.

About TestGorilla

Imagine a world where everyone lands their dream job. TestGorilla is revolutionizing the hiring process through skills-based hiring, empowering one billion people to do just that. Our platform provides scientifically validated tests, enabling companies to hire faster and without bias, based on true skills and potential. We also empower candidates to showcase their abilities and find ideal roles.

At TestGorilla, we stand for diversity, act with integrity, and put talent first. We celebrate individuality and creativity and believe in a workplace where you can make a big impact. Our team works in a flexible, autonomous environment with a focus on well-being and results.

Join us in creating a future where skills matter most, and everyone has the chance to land their dream job.

About the role

We are looking for an adaptable senior machine learning engineer with proven skills and experience in developing machine learning solutions from ideation through to production, deployment and maintenance of models.

Your core tasks involve creating machine learning pipelines to manage model lifecycles using MLOps best practices; managing machine learning and data infrastructure; and experimenting with leveraging LLMs and foundation models. The role is hands-on, delivering high quality maintainable code and will involve close collaboration with product managers, backend engineers and our DevSecOps team.

As an AI-forward company you will directly contribute to TestGorilla’s mission by building and scaling our capabilities across the AI, ML and data stack. We deliver user value, fast. We want you to take your models through deployment and into the world where they can make an impact to help us achieve our vision of helping one billion people land their dream job.

Responsibilities

• Uphold TestGorilla's behaviors and foster an inclusive, supportive culture
• Collaborate effectively with global colleagues across teams and time zones
• Designing, building, deploying, and maintaining scalable machine learning solutions for our clients and internal users
• Developing and managing MLOps pipelines for model training, deployment, monitoring, and iteration
• Implementing best practices for versioning (data, code, models), experiment tracking, and reproducibility in ML workflows
• Working with infrastructure as code (in Terraform + AWS) to support both data and ML systems
• Integrating ML solutions with Generative AI and frameworks like LangChain (e.g., for enhanced analytics, RAG systems, or new product features)
• Triaging reporting and data-related requests from different departments, providing insights and solutions to help teams make data driven decisions
• Staying abreast of the latest advancements in MLOps, Generative AI, and LLM technologies, and driving their adoption where beneficial.Integrating and operationalizing AI/ML models (esp. via APIs and LLMs)

What you’ll bring

We're looking for someone who:

• Is passionate about TestGorilla's mission to help one billion people find their dream jobs
• Has strong written and verbal communication skills in English, with the ability to articulate complex technical concepts (including ML/AI) in plain English
• Thrives in a fast-paced, remote-first environment and can drive initiatives with autonomy with minimal direction
• Has skills and experience developing machine learning solutions from scratch using frameworks such as TensorFlow, PyTorch or SKLearn
• Has advanced proficiency in Python and a strong command of SQL, particularly for data engineering, MLOps, and ML applications
• Has skills and experience with recommender system
• Has hands-on skills and experience with Generative AI, including practical application in areas like prompt engineering, fine-tuning, or Retrieval Augmented Generation (RAG)
• Possesses strong experience in MLOps, including model deployment, monitoring, CI/CD for ML, and lifecycle management (e.g., using tools like Sagemaker, MLflow, Kubeflow, or custom solutions)
• Has skills and previous experience implementing ETL/ELT data pipelines
• Has skills and previous experience with infrastructure as code (e.g., Terraform, CloudFormation)
• Is good at stakeholder management and organizing requests in a dynamic environment.Experience deploying or integrating AI/ML models/services (e.g., using APIs, understanding MLOps fundamentals)

We actively seek diversity and encourage