Job Description

Senior Machine Learning Engineer

Position Overview

We are seeking a Senior Machine Learning Engineer to design, build, deploy, and scale machine learning solutions that solve complex business and technical problems.

This role will work at the intersection of machine learning, software engineering, data, and artificial intelligence, taking models from experimentation through production. The ideal candidate combines strong ML expertise with excellent software engineering skills and experience building reliable, scalable production systems.

Key Responsibilities

Design, develop, and deploy machine learning models and AI-powered applications into production

Build end-to-end ML pipelines covering data preparation, feature engineering, model training, evaluation, deployment, and monitoring

Develop solutions using supervised and unsupervised learning, deep learning, NLP, recommendation systems, and/or Generative AI

Build and optimize applications leveraging Large Language Models (LLMs)

Develop solutions involving RAG, embeddings, vector search, fine-tuning, and prompt/model optimization

Train, evaluate, fine-tune, and optimize machine learning models

Develop production-quality software primarily using Python

Work with ML frameworks such as PyTorch, TensorFlow, scikit-learn, or JAX

Deploy and operate models in cloud environments such as AWS, Azure, or GCP

Build scalable APIs and services for real-time and batch model inference

Partner with Data Scientists, Data Engineers, Software Engineers, and Product teams to translate business problems into ML solutions

Establish model evaluation, testing, monitoring, and performance standards

Improve model accuracy, latency, scalability, reliability, and cost efficiency

Mentor engineers and contribute to ML engineering standards, architecture, and best practices

Evaluate emerging AI/ML technologies and determine where they can provide meaningful business value

Required Qualifications

5+ years of professional experience in Machine Learning Engineering, Software Engineering, Data Science, or a related technical field

Strong programming experience with Python

Demonstrated experience developing and deploying machine learning models into production

Strong knowledge of machine learning algorithms, statistics, model evaluation, and feature engineering

Experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn

Experience building scalable production software and APIs

Experience with AWS, Azure, and/or GCP

Strong understanding of data structures, algorithms, software engineering principles, and distributed systems

Experience with SQL and large-scale data processing

Experience with containerization and deployment technologies such as Docker and Kubernetes

Strong communication skills and ability to collaborate across engineering, data, and product teams

Preferred Qualifications

Experience building production Generative AI and LLM applications

Experience with RAG, embeddings, vector databases, prompt engineering, and LLM evaluation

Experience fine-tuning or adapting foundation models

Experience with Hugging Face, LangChain, LlamaIndex, OpenAI-compatible APIs, or similar AI development frameworks

Experience with MLOps technologies such as MLflow, Kubeflow, SageMaker, Vertex AI, or Azure Machine Learning

Experience with distributed computing technologies such as Spark or Ray

Experience building recommendation, ranking, search, NLP, or computer vision systems

Experience with model serving and inference optimization

Familiarity with GPU computing and CUDA

Experience mentoring junior engineers or providing technical leadership

What Success Looks Like

The Senior Machine Learning Engineer will help turn AI and machine learning concepts into reliable, scalable, production-ready products. Success means building models that don't simply perform well in experimentation, but deliver measurable business outcomes in production while meeting standards for performance, reliability, scalability, and maintainability.

Required Skills