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Junior Machine Learning Engineer
ALSJunior Machine Learning Engineer developing cloud-based AI, LLM, and Agentic AI solutions for ALS, a global scientific testing provider. Supporting model deployment, pipelines, and data-driven workflows.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing and deploying machine learning and AI models, with a strong focus on Large Language Models (LLMs) and cloud-based AI services. Proficient in collaborating with cross-functional teams to enhance model performance and adhere to security and governance standards.
Highest-signal resume keywords
Machine Learning Model DevelopmentLarge Language Models (LLMs)Google Cloud Platform (GCP)Deep Learning Frameworks (PyTorch, TensorFlow)MLOps Tools
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningDeep LearningPython ProgrammingFeature EngineeringModel EvaluationData PreparationAPIs IntegrationContainerization (Docker)Version ControlCI/CD
Soft Skills
Analytical ThinkingProblem-SolvingCollaborationWillingness to Learn
Tools & Technologies
AzureGoogle Cloud Platform (GCP)AWSScikit-learnPandasNumPyVector DatabasesRetrieval-Augmented Generation (RAG)MicroservicesAgentic AI Concepts
Certifications & Qualifications
Degree in Computer ScienceDegree in Data ScienceDegree in Software EngineeringDegree in Machine LearningDegree in Artificial Intelligence
Industry Keywords
AI SolutionsTask AutomationOrchestration WorkflowsData GovernanceResponsible AI Practices
Tech Stack
Tools & technologiesAWSAzureCloudDockerGoogle Cloud PlatformMicroservicesNumpyPandasPythonPyTorchScikit-LearnTensorflow
About the role
Key responsibilities & impact- Support the development and deployment of machine learning and AI models across ALS business functions
- Assist in building AI solutions using Large Language Models (LLMs)
- Contribute to Agentic AI systems, including tool-using agents, orchestration workflows, and task automation
- Develop, train, test, and evaluate conventional machine learning and deep learning models
- Work with structured and unstructured data for model development, feature engineering, and data preparation
- Collaborate with senior AI engineers and data scientists to improve model performance, reliability, scalability, and maintainability
- Support cloud-based AI and ML development using Azure, Google Cloud Platform (GCP), and AWS
- Assist in building model pipelines, experimentation workflows, and deployment processes
- Participate in code reviews, technical documentation, testing, and quality assurance activities
- Stay current with emerging trends in machine learning, generative AI, LLMs, deep learning, and cloud AI services
- Follow ALS standards for security, privacy, data governance, and responsible AI practices
Requirements
What you’ll need- Hands-on experience with Google Cloud Platform (GCP)
- Experience using cloud AI and machine learning services, model hosting, or MLOps tools
- Familiarity with vector databases, embeddings, retrieval-augmented generation (RAG), or semantic search
- Experience with APIs, microservices, or integrating machine learning models into applications
- Knowledge of version control, testing, CI/CD, and documentation
- Exposure to containerization tools such as Docker
- Experience working with enterprise data environments or cross-functional technical teams
- Degree or diploma in Computer Science, Data Science, Software Engineering, Machine Learning, Artificial Intelligence, or a related technical discipline
- Practical experience with machine learning, including model training, evaluation, and deployment concepts
- Experience with deep learning frameworks such as PyTorch or TensorFlow
- Exposure to Large Language Models (LLMs)
- Familiarity with Agentic AI concepts, including autonomous agents, tool calling, workflow orchestration, and AI assistants
- Programming experience in Python
- Familiarity with scikit-learn, pandas, NumPy, or similar libraries
- Experience with at least one major cloud platform, including Azure, Google Cloud Platform (GCP), or AWS
- Ability to work effectively in a collaborative, hybrid team environment
- Strong analytical thinking and problem-solving skills
- Willingness to learn
- Ability to sit at a desk and perform general office work for extended periods, with periodic computer/screen use
- Must be a citizen or permanent resident of the country applied for, or hold or be able to obtain a valid working visa
Benefits
Comp & perks- Structured wage increases
- Comprehensive benefit package including extended medical, dental, and vision coverage
- Access to company perks
- Life and disability insurance
- Retirement plan with company match
- Employee assistance and wellness programs
- Additional vacation days for years of service
- Business support for education or training after 9 months with the company
- Learning & development opportunities, including unlimited access to e-learnings