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AI/ML Engineer (Dallas)
AI/ML Engineer (Dallas)Apexon • Dallas, TX, United States
AI / ML Engineer (Dallas)

AI / ML Engineer (Dallas)

Apexon • Dallas, TX, United States
[job_card.variable_hours_ago]
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  • [job_card.full_time]
[job_card.job_description]

About the Role

Apexon is seeking an experienced AI / ML Engineer with strong expertise in LLM development, MLOps, and building scalable GenAI solutions . You will design, build, and operationalize AI / ML systems that support enterprise clients across healthcare, BFSI, retail, and digital transformation engagements.

The ideal candidate has hands-on experience building end-to-end machine learning pipelines , optimizing large language model workflows , and deploying secure ML systems in production environments.

Responsibilities

LLM & AI Solution Development

  • Build, fine-tune, evaluate, and optimize Large Language Models (LLMs) for client-specific use cases such as document intelligence, chatbot automation, code generation, and workflow orchestration.
  • Develop RAG (Retrieval-Augmented Generation) pipelines using enterprise knowledge bases.
  • Implement prompt engineering, guardrails, hallucination reduction strategies, and safety frameworks.
  • Work with transformer-based architectures (GPT, LLaMA, Mistral, Falcon, etc.) and develop optimized model variants for low-latency and cost-efficient inference.

Machine Learning Engineering

  • Develop scalable ML systems including feature pipelines, training jobs, and batch / real-time inference services.
  • Build and automate training, validation, and monitoring workflows for predictive and GenAI models.
  • Perform offline evaluation, A / B testing, performance benchmarking, and business KPI tracking.
  • MLOps & Platform Engineering

  • Build and maintain end-to-end MLOps pipelines using :
  • AWS SageMaker, Databricks, MLflow, Kubernetes, Docker, Terraform, Airflow
  • Manage CICD pipelines for model deployment, versioning, reproducibility, and governance.
  • Implement enterprise-grade model monitoring (data drift, performance, cost, safety).
  • Maintain infrastructure for vector stores, embeddings pipelines, feature stores, and inference endpoints.
  • Data Engineering & Infrastructure

  • Build data pipelines for structured and unstructured data using :
  • Snowflake, S3, Kafka, Delta Lake, Spark (PySpark)
  • Work on data ingestion, transformation, quality checks, cataloging, and secure storage.
  • Ensure all systems adhere to Apexon and client-specific security, IAM, and compliance standards.
  • Cross-Functional Collaboration

  • Partner with product managers, data engineers, cloud architects, and QA teams.
  • Translate business requirements into scalable AI / ML solutions.
  • Ensure model explainability, governance documentation, and compliance adherence.
  • Basic Qualifications

  • Bachelors or Masters degree in Computer Science, Engineering, AI / ML, Data Science, or related field.
  • 4+ years of experience in AI / ML engineering , including 1+ years working with LLMs / GenAI .
  • Strong experience with Python , Transformers , PyTorch / TensorFlow , and NLP frameworks.
  • Hands-on expertise with MLOps platforms : SageMaker, MLflow, Databricks, Kubernetes, Docker .
  • Strong SQL and data engineering experience (Snowflake, S3, Spark, Kafka).
  • Preferred Qualifications

  • Experience implementing Generative AI solutions for enterprise clients.
  • Expertise in distributed training, quantization, optimization, and GPU acceleration.
  • Experience with :
  • Vector Databases (Pinecone, Weaviate, FAISS)
  • RAG frameworks (LangChain, LlamaIndex)
  • Monitoring tools (Prometheus, Grafana, CloudWatch)
  • Understanding of model governance, fairness evaluation, and client compliance frameworks.
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