Machine Learning Engineer (AI)

Location: Remote, USA. Applicants must already be authorized to work for any employer in the United States; visa sponsorship is not available.

Company

Full-service consulting firm delivering data, software, and technology solutions for clients.

What you will do

• Design, train, deploy, monitor, and retrain ML models for text classification, entity extraction, clustering, narrative detection, and topic detection.
• Build LLM-powered features using prompt design, retrieval-augmented generation, and agentic workflows.
• Develop embedding and semantic-search pipelines to group related content and identify emerging online threats.
• Productionize scalable ML services with measurable latency, cost, accuracy, and reliability targets.
• Build evaluation frameworks and datasets to measure quality, bias, and model drift.
• Collaborate with data engineering, backend engineering, and product stakeholders on high-volume, noisy, multilingual text data.

Requirements

• 4+ years of professional experience building and deploying machine learning models in production.
• Strong Python skills and hands-on experience with PyTorch, TensorFlow, or Hugging Face Transformers.
• Practical NLP experience with classification, named entity recognition, topic modeling, or semantic similarity.
• Hands-on experience with LLMs, prompt engineering, RAG, embeddings, and vector search.
• Experience deploying and operating ML services on AWS, GCP, or Azure using Docker and CI/CD.
• Strong understanding of model evaluation, error analysis, production monitoring, and communication in remote cross-functional teams.

Nice to have

• Experience with trust and safety, threat intelligence, disinformation research, or social media data.
• Experience with agentic AI systems, multilingual NLP, or LLM fine-tuning with LoRA or PEFT.
• Familiarity with MLflow, SageMaker, Vertex AI, Weights & Biases, Kafka, Spark, or Airflow.

Culture & Benefits

• Remote, cross-functional work with data engineers, backend engineers, and product stakeholders.
• Project-based contract assignment focused on an AI-powered risk intelligence platform.
• Work on systems addressing disinformation, reputational attacks, emerging online threats, and security risks.