Note: The job is a remote job and is open to candidates in USA. Tech Holding is seeking a hands-on Machine Learning Engineer for a project assignment building an AI-powered risk intelligence platform. The role involves designing, deploying, and evaluating NLP and LLM-based models that help enterprises detect and respond to emerging online threats, working with data engineers, backend engineers, and product stakeholders.
Responsibilities
- Design, train, and deploy ML models for text classification, entity extraction, clustering, and narrative and topic detection
- Build and improve LLM-powered features, including prompt design, retrieval-augmented generation (RAG), and agentic workflows
- Develop embedding and semantic-search pipelines to group related content and surface emerging threats
- Productionize models as scalable, monitored services with clear latency, cost, and accuracy targets
- Build evaluation frameworks and datasets to measure model quality, bias, and drift over time
- Work with data engineering to improve ingestion, labeling, and feature pipelines for high-volume, noisy, multilingual text data
- Monitor and retrain models in production, and debug quality issues end to end
- Document approaches and share trade-offs clearly with technical and non-technical stakeholders
Skills
- 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, such as classification, named entity recognition (NER), topic modeling, or semantic similarity on real-world text data
- Hands-on experience building with LLMs (OpenAI, Anthropic, or open-source models), including prompt engineering and RAG
- Experience with embeddings and vector search (e.g., pgvector, Pinecone, OpenSearch, or FAISS)
- Experience deploying and operating ML services on AWS, GCP, or Azure, using Docker and CI/CD
- Solid grasp of model evaluation, including metrics, test sets, error analysis, and production monitoring
- Strong communication skills
- Authorized to work for ANY employer in the U.S
- Unable to sponsor or take over sponsorship of an employment Visa at this time
- Experience with trust and safety, threat intelligence, disinformation research, or social media data
- Experience building agentic AI systems or tool-using LLM workflows (e.g., LangChain, LlamaIndex, or custom frameworks)
- Experience with multilingual NLP
- Familiarity with MLOps tooling such as MLflow, SageMaker, Vertex AI, or Weights & Biases
- Experience with streaming or large-scale data processing (e.g., Kafka, Spark, or Airflow)
- Experience fine-tuning LLMs (LoRA or PEFT) or distilling models to cut cost and latency
Benefits
- Remote work in the USA
Company Overview