AI/ML Consultant

Job Title: AI/ML Consultant

Location: Dallas or Austin, TX (Hybrid 2 3 days onsite)

Mode: W2 only

Overview: We are seeking a highly skilled AI/ML Consultant to join our advanced analytics and data science team. This role is ideal for someone who thrives at the intersection of machine learning, data engineering, and business strategy. You will work with cross-functional teams to design, develop, and deploy AI/ML models and GenAI solutions that drive measurable business outcomes.

Key Responsibilities

• Collaborate with business stakeholders to identify high-impact AI/ML use cases across domains (e.g., fraud detection, personalization, forecasting, NLP).
• Design and implement end-to-end ML pipelines: data ingestion, feature engineering, model training, validation, deployment, and monitoring.
• Develop and fine-tune models using scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch, or Hugging Face Transformers.
• Architect and deploy LLM-based solutions (e.g., RAG, prompt engineering, fine-tuning) using OpenAI, Claude, Cohere, or open-source models.
• Integrate models into production using MLOps tools like MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML.
• Work with data engineers to ensure scalable data pipelines using Spark, Databricks, Snowflake, or BigQuery.
• Ensure compliance with model governance, explainability, and fairness standards (e.g., SHAP, LIME, AI Fairness 360).
• Present findings and model insights to technical and non-technical stakeholders.

Required Skills

• 10 years of experience in machine learning, data science, or applied AI.
• Strong programming skills in Python (Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow).
• Experience with LLMs and GenAI frameworks (LangChain, RAG, vector databases like FAISS, Pinecone, Weaviate).
• Proficiency in SQL and working with large-scale data platforms (Snowflake, Databricks, Redshift).
• Familiarity with cloud platforms: AWS, Azure, or Google Cloud Platform.
• Experience with CI/CD for ML, containerization (Docker), and orchestration (Airflow, Kubernetes).
• Strong understanding of statistics, probability, and optimization techniques.

Preferred Qualifications

• Master's or Ph.D. in Computer Science, Data Science, Statistics, or related field.
• Experience in regulated industries (finance, healthcare) with model risk management.

Certifications: AWS Certified Machine Learning Specialty, Azure AI Engineer Associate, or equivalent

LGL Tech is a trusted technology partner specializing in Software Development, Product Engineering, and IT Services. We provide comprehensive solutions and strategic advisory services to businesses worldwide, from mid-market enterprises to Fortune 100 companies.

With expertise in ERP, SaaS, AI/ML, cloud computing, infrastructure management, and cybersecurity, we help businesses modernize operations, streamline processes, and drive digital transformation.

Balancing innovation with managing legacy systems and mitigating security risks is critical in today s digital world. LGL Tech delivers tailored software solutions, scalable IT services, and strategic technology approaches that accelerate growth and ensure long-term success.

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