Gen AI Engineer - Full Time

NeerInfo Solutions Pvt. Ltd.; Plano (TX); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Long-term Disability

Health and Dependent Care Reimb. A/cs

Insurance (Accident, Critical Illness,

401(k) plan

Job summary

NeerInfo Solutions Pvt. Ltd. is seeking a Data Science Consultant 2 in Plano, TX. You will develop data preparation tasks, build forecasting and ML models, and ensure readiness for production deployment with scalable, reliable performance.

The role involves deploying models, validating results, and guiding best practices across the team. Strong Python, ML framework, and MLOps familiarity are required to drive analytic solutions forward.

Qualifications

• Hands-on experience with major ML frameworks (PyTorch, TensorFlow, Keras).
• Familiarity with LLMs, prompt engineering, and fine‑tuning (LoRA, QLoRA).
• Exposure to RAG systems and hybrid search techniques.
• Understanding of model deployment and containerization (Docker).
• Proficiency in Python for AI development, data preprocessing, and scripting.
• Experience with generative AI tools (LangChain, Hugging Face, LlamaIndex).
• Understanding of Git for version control.
• Awareness of AI compliance, data privacy, and responsible AI principles.

Responsibilities

• Develop data preparation tasks and ensure data readiness for modeling.
• Build, evaluate, and deploy predictive models and data-driven analyses.
• Refine algorithms for business needs and deploy into production-ready solutions.
• Test and optimize algorithms for performance, reliability, and scalability.

Skills

PyTorch

TensorFlow

Keras

Python

LLMs

Prompt engineering

LoRA / Fine-tuning

Docker

Git

LangChain

Hugging Face

LlamaIndex

RAG systems

BigQuery

Hadoop

SageMaker

Snowflake

Tools

Docker

Git

SageMaker

Snowflake

BigQuery

Hadoop

Job description

In the assigned Job Role of Data Science Consultant 2, your Area Of Responsibility will be as below:

Develop data preparation tasks, while identifying patterns or anomalies.

Ensure data readiness for advanced modeling.

Develop models for complex use cases (e.g., forecasting models, LLM-based solutions), while refining algorithms to meet business needs, and ensure smooth deployment into scalable, production-ready solutions.

Conduct testing and optimize algorithms for performance, reliability, and scalability, while providing guidance to team members in best practices.

Design and develop predictive models and data-driven analyses to address business challenges.

Build, evaluate, and deploy models, standardize code, and contribute to knowledge management.

Leverage tools like SAS and R/Python to create reusable customizations for non-ML, ML, and deep learning algorithms, while enhancing analytics including LLMs, and create innovative, cost-effective solutions.

Define analytics problems for projects; execute visualization, analysis, and predictive modeling under guidance.

Proactively maintain models and implement improvements for accuracy and reliability.

Apply governance controls to mitigate risks and ensure compliance.

Analyze performance trends, recommend improvements, and document discrepancies for escalation.

Maintain comprehensive documentation standards, while participating in knowledge transfer sessions.

Participate in discussions with stakeholders to refine requirements, provide insights, and guide implementation of models.

Apply the predefined quality measurement framework at an individual task level in the project.

Deploy complex analytics tools or multi-system integration, while validating deployment success.

Participate in developing scripts or templates for repeated deployments tasks.

Contribute to analytic solutions, IP asset creation, and training initiatives.

Contribute to thought leadership such as papers, innovative non-ML, ML, deep learning or LLM models, and proofs of concepts.

Participate in and deliver analytics training, while contributing to content creation.

Provide input for segment and unit-level business plans.

Your contribution to the team:

Deliver scalable, high-quality analytics solutions aligned to business needs.

A knack for optimization, deployment and performance improvement of models.

The ability to drive innovation through advanced analytics, automation and thought leadership.

Enable team growth through knowledge sharing, training and standardization.

Support business planning with data-driven insights.

Required Skill and Experience

Hands-on experience with at least one major machine learning framework (PyTorch, TensorFlow, Keras).

Familiarity with LLMs, prompt engineering, and fine-tuning (e.g., LoRA, QLoRA).

Exposure to RAG systems and basic knowledge of hybrid search techniques.

Understanding of model deployment and containerization (Docker).

Proficiency in Python for AI development, data preprocessing, and scripting.

Experience with generative AI tools (LangChain, Hugging Face, LlamaIndex) is a plus.

Understanding of version control systems (Git).

Awareness of AI compliance, data privacy, and responsible AI principles.

Preferred Skill and Experience

Experience in Big Data technologies (e.g., BigQuery, Hadoop), ML model development, data engineering, and software engineering principles. Knowledge of MLOps and AI/ML deployment (e.g., SageMaker, Snowflake). Familiarity with CI/CD, DevOps, and automation tools in AI/ML contexts.

EEO/About Us

Along with competitive pay, as a full-time employee you are also eligible for the following benefits:

• Long-term/Short-term Disability
• Health and Dependent Care Reimbursement Accounts
• Insurance (Accident, Critical Illness , Hospital Indemnity, Legal)
• 401(k) plan and contributions dependent on salary level