The Role
Design, build, and operate end-to-end data and AI systems: scalable ETL pipelines, model development and deployment, backend services/APIs, cloud infrastructure, MLOps, data governance, and lead technical reviews while mentoring engineers and collaborating with stakeholders.
Summary Generated by Built In
Role Summary
Senior AI/Data Engineer at GeniusXLab responsible for designing, building, and operating end-to-end data and AI systems for consulting and product engagements, including data pipelines, machine learning models, and production-grade APIs across cloud environments.workable+3
Key Responsibilities
- Design and implement scalable data ingestion, ETL/ELT, and transformation pipelines to power AI, analytics, and real-time platforms for GeniusXLab clients.workable+2
- Build, train, evaluate, and retrain machine learning models using Python and modern ML frameworks; own experimentation, performance tuning, and deployment readiness.fullstack+1
- Develop and maintain backend services and APIs in Java or .NET (and/or Python) to serve models and integrate AI capabilities into SaaS and enterprise systems.mortenson+2
- Architect and manage cloud infrastructure (AWS, Azure, GCP) for data processing, model training, and real-time inference, following GeniusXLab’s cloud-native best practices.mortenson+3
- Implement MLOps practices, including CI/CD, automated deployment, observability, and incident response for AI workloads in production.mortenson+2
- Collaborate with product managers, data scientists, software engineers, and client stakeholders to translate business requirements into AI/data solutions that align with GeniusXLab’s consulting approach.montecarlo+2
- Ensure data quality, governance, security, and compliance (e.g., HIPAA/GDPR) across sensitive datasets, especially in sectors like healthcare, finance, and manufacturing.montecarlo+2
- Lead technical design reviews, mentor junior engineers, and contribute to GeniusXLab’s internal AI platform and engineering standards.montecarlo+2
Required Skills
- 8–10 years of experience across software engineering, data engineering, and AI/ML, with a track record of shipping production systems.workable+2
- Strong proficiency in Python and SQL; solid experience with Java or .NET for backend and API development.montecarlo+1
- Hands-on experience with data pipelines and orchestration (e.g., Spark, Kafka, Airflow or equivalent) and both relational and NoSQL databases.curatepartners+2
- Practical experience with ML frameworks (Scikit-learn, TensorFlow, PyTorch) and deploying models as reliable services.fullstack+1
- Solid understanding of statistics, probability, and applied mathematics for model development, evaluation, and A/B testing.geeksforgeeks+1
- Familiarity with NLP and/or GenAI (LLMs, RAG, agents) used in real-world applications is a strong plus.montecarlo+2
- Excellent communication skills, ability to work in cross-functional, consulting-driven teams, and strong business acumen.getdbt+2
Education
- Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or related field.
- Master’s degree preferred; relevant AI/ML, cloud, or data certifications are a plus.artisantalent+1
Application & Scam/Risk Notice
To protect candidates and GeniusXLab from scams and impersonation:
- All resumes and candidate materials must be sent directly to: [email protected].montecarlo
- GeniusXLab will never request payment, banking information, or personal documents (passport, SSN, etc.) during initial screening.
- If you receive a message claiming to represent GeniusXLab from a different email or asking for money or confidential data, do not respond; forward it to [email protected] for verification.
Skills Required
- 8–10 years of experience across software engineering, data engineering, and AI/ML with production systems delivered.
- Strong proficiency in Python.
- Strong proficiency in SQL.
- Solid experience with Java or .NET for backend and API development (and/or Python).
- Hands-on experience with data pipelines and orchestration (e.g., Spark, Kafka, Airflow or equivalent).
- Experience with relational and NoSQL databases.
- Practical experience with ML frameworks (Scikit-learn, TensorFlow, PyTorch) and model deployment.
- Solid understanding of statistics, probability, and applied mathematics for model development and evaluation.
- Experience architecting and managing cloud infrastructure (AWS, Azure, GCP) for data and model workloads.
- Experience implementing MLOps practices including CI/CD, automated deployment, observability, and incident response.
- Excellent communication skills and ability to work in cross-functional, consulting-driven teams.
- Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or related field.
- Master’s degree preferred; relevant AI/ML, cloud, or data certifications are a plus.
- Familiarity with NLP and/or GenAI (LLMs, RAG, agents).
Am I A Good Fit?
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company









