AI/ML Engineer | Talent Marketplace

Summary

Lago operates the HireLago Talent Marketplace, connecting vetted professionals with remote opportunities at companies worldwide. The AI/ML Engineer designs, develops, deploys, and monitors machine learning models and AI-powered systems across the full machine learning lifecycle. The role collaborates with data, product, and engineering teams to deliver accurate, reliable, and scalable AI solutions.

Responsibilities

• Design, develop, and deploy machine learning models for classification, regression, NLP, computer vision, recommendation, or other applicable use cases
• Work with data engineers to build and maintain data pipelines that feed ML model training and inference
• Evaluate and select appropriate algorithms, frameworks, and architectures for each problem
• Train, validate, and fine-tune models using best practices for avoiding overfitting and ensuring generalization
• Deploy models to production environments and build robust inference pipelines
• Monitor model performance post-deployment and implement strategies for model retraining and drift detection
• Collaborate with product and engineering teams to integrate AI features into applications
• Conduct experiments, document findings, and present insights to technical and non-technical stakeholders
• Stay current with advances in AI/ML research and assess applicability to the business
• Contribute to MLOps practices, tooling, and infrastructure

Skills

• 3–5 years of experience in machine learning engineering, data science, or a related field
• Proficiency in Python and core ML libraries (scikit-learn, TensorFlow, PyTorch, or similar)
• Strong understanding of machine learning fundamentals (supervised/unsupervised learning, model evaluation, feature engineering)
• Experience deploying ML models to production environments (APIs, batch pipelines, or embedded systems)
• Familiarity with data manipulation and analysis (Pandas, NumPy, SQL)
• Solid software engineering practices - version control, testing, and code quality
• Strong analytical and problem-solving skills
• Experience with LLMs, prompt engineering, and generative AI applications (OpenAI, Anthropic, LangChain, or similar)
• Familiarity with MLOps platforms (MLflow, Weights & Biases, SageMaker, Vertex AI, or similar)
• Experience with cloud ML infrastructure (AWS, GCP, or Azure AI/ML services)
• Knowledge of data engineering tools and pipelines (Spark, Airflow, dbt, or similar)
• Experience with NLP techniques (transformers, embeddings, RAG pipelines)
• Advanced degree (M.S. or Ph.D.) in Computer Science, Statistics, or a related field

Qualifications

Must Haves

• 3–5 years of experience in machine learning engineering, data science, or a related field
• Proficiency in Python and core ML libraries (scikit-learn, TensorFlow, PyTorch, or similar)
• Strong understanding of machine learning fundamentals (supervised/unsupervised learning, model evaluation, feature engineering)
• Experience deploying ML models to production environments (APIs, batch pipelines, or embedded systems)
• Familiarity with data manipulation and analysis (Pandas, NumPy, SQL)
• Solid software engineering practices - version control, testing, and code quality
• Strong analytical and problem-solving skills

Nice to Haves

• Experience with LLMs, prompt engineering, and generative AI applications (OpenAI, Anthropic, LangChain, or similar)
• Familiarity with MLOps platforms (MLflow, Weights & Biases, SageMaker, Vertex AI, or similar)
• Experience with cloud ML infrastructure (AWS, GCP, or Azure AI/ML services)
• Knowledge of data engineering tools and pipelines (Spark, Airflow, dbt, or similar)
• Experience with NLP techniques (transformers, embeddings, RAG pipelines)
• Advanced degree (M.S. or Ph.D.) in Computer Science, Statistics, or a related field

Benefits

• Become a Certified Professional through our vetting process.
• Showcase your profile on the HireLago Talent Marketplace.
• Gain access to exclusive remote opportunities before they're publicly advertised.
• Get matched with roles that fit your skills, experience, schedule, and salary expectations.
• Build long-term career opportunities through our growing global employer network.
• 100% free for professionals, with no placement fees, subscriptions, or hidden costs.