Senior AI Engineer/Data Scientist

KANINI Software Solutions PTE Ltd.; Nashville (TN); On-site; USD 140,000 - 190,000; Full time

Job summary

Kanini Software Solutions, Inc. in Nashville seeks a pioneering Senior AI Engineer/Data Scientist to own the complete data science lifecycle for our flagship prediction model project. This mission-critical role puts one expert at the center of sourcing, analyzing, and engineering all data powering predictive models.

The candidate will operate independently with minimal supervision, combining deep AI/ML mastery with hands-on engineering and business acumen to deliver production-grade outcomes.

Qualifications

• 5+ years hands-on data science with at least 2 years delivering production-grade ML models.
• Ability to own end-to-end data science projects independently.
• Portfolio demonstrating predictive modeling and measurable business impact.
• Kaggle rankings, research publications, or open-source ML contributions are a strong plus.
• Experience in fast-paced, data-driven decision environments.

Responsibilities

• Lead end-to-end analysis of large, multi-source datasets to surface patterns for model inputs.
• Identify, collect, clean, validate, and transform data for model consumption.
• Design and maintain scalable data pipelines (training, validation, inference).
• Develop and deploy ML models via REST APIs; monitor in production.

Skills

Python

SQL

Data science

TensorFlow

PyTorch

NLP

MLOps

Docker

Kubernetes

REST APIs

Education

PhD in CS/Statistics/Math

MS in CS or related

BSc equivalent with strong research

Tools

Kubeflow

MLflow

Snowflake

FastAPI

Flask

Job description

Job description We are hiringapioneering, fully autonomous Senior AI Engineer/Data Scientisttoown the complete data science lifecycle for our flagship prediction modelproject. This role ismission-critical— the candidate will bethe single point of expertise responsible for sourcing, analyzing, andengineering all data that powers our predictive models. Operating independentlywith minimal supervision, this individual must combinedeep AI/MLmastery, hands-on engineering skills, and sharp business acumentodeliver measurable, production-grade outcomes.

KeyResponsibilities:

DataAnalysis & Pipeline Ownership

• Lead end-to-end analysis of large, complex, multi-source datasets to surfacepatterns driving model inputs
• Identify, collect, clean, validate, and transform all data required forprediction model consumption
• Design and maintain scalable, production-grade data pipelines (training,validation, inference)
• Perform deep EDA, data profiling, and quality audits to ensure model-ready datastandards

PredictiveModeling & AI/ML

• Architect, train, evaluate, and iterate ML models — supervised, unsupervised,and reinforcement learning
• Own feature engineering: selection, extraction, transformation, anddimensionality reduction
• Apply advanced techniques: deep learning, NLP, time-series forecasting,ensemble methods
• Benchmark, A/B test, and monitor models in production; drive continuousperformance improvement
• Deploy models via REST APIs (FastAPI/Flask); ensure reproducibility andscalability
• Self-direct from problem definition through solution delivery with zerohand-holding
• Communicate model results and data insights clearly to technical andnon-technical stakeholders
• Document all experiments, methodologies, and outcomes — audit-ready andreproducible
• Champion best practices across the data science lifecycle; mentor junior teammembers

QUALIFICATIONS

• B.S./M.S./Ph.D.in Computer Science, Statistics, Mathematics, or equivalent quantitative field(Master’s/Ph.D. strongly preferred)
• 5 years of hands-on data science experience with at least 2 years deliveringproduction-grade ML models
• Provenability to own and deliver end-to-end data science projects independently
• Portfoliodemonstrating innovation in predictive modeling and measurable businessimpact
• Kagglerankings, research publications, or open-source ML contributions are a strongplus
• Experiencein a fast-paced, data-driven, decision-model environment

REQUIREDSKILLS & QUALIFICATIONS

Core DataScience & Mathematics

• Statistics(Bayesian inference, hypothesis testing, regression, distributions)
• Linearalgebra, calculus, and probability applied to ML model design
• Supervised& unsupervised learning, anomaly detection, clustering

Programming& Development

• Python(Expert): NumPy, Pandas, Scikit-learn,Statsmodels,Matplotlib,Plotly
• SQL(Advanced): window functions, CTEs, query optimization
• Git/ GitHub; CI/CD for ML;MLOpswithMLflowor Kubeflow
• Docker& Kubernetes for model containerization and serving

AI / MLFrameworks (Must-Have)

• TensorFlowand/orPyTorch— deep learning architectures
• HuggingFace Transformers — NLP, LLMs, and fine-tuning
• SHAP,LIME — model explainability and interpretability

Snowflake(Good to Have)

• SnowflakeData Cloud: querying, Snowpark for Python ML pipelines
• SnowflakeCortex AI / ML Functions for in-database ML
• dbtfordata transformation; data governance within Snowflake

Kanini Software Solutions, Inc. does not discriminate in employment matters on the basis of race, gender, religion, age, national origin, citizenship, veteran status, family status, disability status, or any other protected class. We support workplace diversity. If you have a disability, please let us know if there is anything we can do to improve the interview process for you; we’re happy to accommodate. Kanini Software Solutions, Inc., 25 Century Blvd., Ste. 602, Nashville, TN 37214.

Automation, Cloud, AI-driven Insights — more than “Dreams of the Future” these have become the “Demands of the Present”, to set the stage for a business to be truly digital.