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Hi there! I'm Satish Kumar Reddy, an AI/ML engineer with 4+ years of experience designing, developing, and deploying end-to-end machine learning and AI solutions across manufacturing, automation, and enterprise domains. I enjoy turning messy data into scalable, data-driven systems that empower teams to make better decisions. I’m passionate about building robust ML/AI pipelines, applying NLP, computer vision, and large language models to real-world problems, and collaborating with cross-functional teams to drive measurable business impact. I strive for clarity, transparency, and knowledge sharing across all stages of the development lifecycle.…Hi there! I'm Satish Kumar Reddy, an AI/ML engineer with 4+ years of experience designing, developing, and deploying end-to-end machine learning and AI solutions across manufacturing, automation, and enterprise domains. I enjoy turning messy data into scalable, data-driven systems that empower teams to make better decisions. I’m passionate about building robust ML/AI pipelines, applying NLP, computer vision, and large language models to real-world problems, and collaborating with cross-functional teams to drive measurable business impact. I strive for clarity, transparency, and knowledge sharing across all stages of the development lifecycle.

Satish Kumar Reddy

Data Scientist, AI Engineer, Developer, +5

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Hi there! I'm Satish Kumar Reddy, an AI/ML engineer with 4+ years of experience designing, developing, and deploying end-to-end machine learning and AI solutions across manufacturing, automation, and enterprise domains. I enjoy turning messy data into scalable, data-driven systems that empower teams to make better decisions. I’m passionate about building robust ML/AI pipelines, applying NLP, computer vision, and large language models to real-world problems, and collaborating with cross-functional teams to drive measurable business impact. I strive for clarity, transparency, and knowledge sharing across all stages of the development lifecycle.…Hi there! I'm Satish Kumar Reddy, an AI/ML engineer with 4+ years of experience designing, developing, and deploying end-to-end machine learning and AI solutions across manufacturing, automation, and enterprise domains. I enjoy turning messy data into scalable, data-driven systems that empower teams to make better decisions. I’m passionate about building robust ML/AI pipelines, applying NLP, computer vision, and large language models to real-world problems, and collaborating with cross-functional teams to drive measurable business impact. I strive for clarity, transparency, and knowledge sharing across all stages of the development lifecycle.

Available to hire

Hi there! I’m Satish Kumar Reddy, an AI/ML engineer with 4+ years of experience designing, developing, and deploying end-to-end machine learning and AI solutions across manufacturing, automation, and enterprise domains.

I enjoy turning messy data into scalable, data-driven systems that empower teams to make better decisions. I’m passionate about building robust ML/AI pipelines, applying NLP, computer vision, and large language models to real-world problems, and collaborating with cross-functional teams to drive measurable business impact. I strive for clarity, transparency, and knowledge sharing across all stages of the development lifecycle.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

AI/ML Engineer at Tungsten Automation

August 1, 2024 - Present

Designed and deployed advanced machine learning models for NLP, predictive analytics, and computer vision, reducing manual effort by 30% and improving workflow accuracy by 25%. Introduced generative AI solutions using Hugging Face, LangChain, and OpenAI APIs, enhancing customer response automation and cutting average query resolution time by 40%. Built and optimized scalable big data pipelines using Spark, Databricks, and BigQuery, ensuring faster access to insights and smoother handling of large datasets. Established robust MLOps workflows with MLflow, Docker, Kubernetes, and Jenkins, enabling seamless model transition from experimentation to production with reduced downtime. Implemented Retrieval-Augmented Generation (RAG) pipelines to augment LLM outputs with domain-specific knowledge, improving response relevance and supporting evidence-based decision-making across teams. Collaborated closely with cross-functional teams in Agile setup, blending strong technical problem-solving skil

Data Scientist at ARAPL

April 30, 2022 - August 29, 2025

Developed and deployed machine learning models (classification, regression, clustering) using Python, Scikit-learn, TensorFlow, and PyTorch, improving automation workflow accuracy by 30%. Built deep learning solutions (CNNs, RNNs, LSTMs) to process sensor data for predictive maintenance, significantly reducing unplanned downtime and optimizing equipment reliability and operational efficiency across manufacturing environments. Designed and implemented computer vision pipelines with YOLO and OpenCV for real-time object detection and robotic tracking, enhancing automation, safety, and production line consistency. Applied NLP techniques with Hugging Face Transformers to analyze unstructured system logs, improving monitoring, error detection, and decision-making efficiency while providing actionable insights for technical teams and business stakeholders. Utilized Apache Spark and Databricks for large-scale data processing and ETL pipelines, reducing data processing time by 35% and improving

Data Analyst

July 31, 2020 - August 29, 2025

Worked closely with business teams to understand reporting needs and translated them into SQL queries and Python scripts, ensuring accurate and timely insights delivered 20% faster for strategic planning and decision-making. Designed interactive dashboards in Tableau and Power BI that provided managers real-time visibility into KPIs, improving decision-making speed by 25% across multiple business units. Applied statistical techniques and hypothesis testing to uncover patterns in sales and operational data, helping optimize business strategies and long-term performance while ensuring consistent data-driven decision-making across functional areas. Automated repetitive reporting tasks using Excel (VLOOKUP, Pivot Tables, Power Pivot) and SQL, cutting manual effort and freeing up time for deeper business-driven analysis, thereby improving overall efficiency, accuracy, and productivity within the organization significantly. Partnered with cross-functional teams to simplify complex datasets i

AI/ML Engineer at Tungsten Automation

August 1, 2024 - Present

Designed and deployed advanced machine learning models for NLP, predictive analytics, and computer vision, significantly reducing manual effort by 30% and improving overall accuracy of critical business workflows by 25%. Introduced Generative AI solutions using Hugging Face, LangChain, and OpenAI APIs, enhancing customer response automation and cutting average query resolution time by 40%. Built and optimized scalable big data pipelines with Spark, Databricks, and BigQuery, ensuring faster insight access and smoother handling of large enterprise-wide datasets. Set up robust MLOps workflows with MLflow, Docker, Kubernetes, and Jenkins, enabling seamless model transitions from experimentation to production with reduced downtime. Implemented Retrieval-Augmented Generation (RAG) pipelines to retrieve domain-specific knowledge from large datasets, improving response relevance and supporting faster, evidence-based decision-making. Collaborated closely with cross-functional teams in a fast-pa

Data Scientist at ARAPL

April 30, 2022 - August 29, 2025

Developed and deployed machine learning models (classification, regression, clustering) using Python, Scikit-learn, TensorFlow, and PyTorch, improving automation workflow accuracy by 30%. Built deep learning solutions (CNNs, RNNs, LSTMs) to process sensor data for predictive maintenance, significantly reducing unplanned downtime and optimizing equipment reliability, operational efficiency, and cost savings across manufacturing. Designed and implemented computer vision pipelines with YOLO and OpenCV for real-time object detection and robotic tracking, enhancing automation, safety, and supporting consistent high-quality production lines. Applied NLP techniques with Hugging Face Transformers to analyze unstructured system logs, improving monitoring, error detection, and decision-making efficiency while providing actionable insights. Utilized Apache Spark and Databricks for large-scale data processing and ETL pipelines, ensuring reliable and timely data availability for modeling, reducing

Data Analyst

July 31, 2020 - August 29, 2025

Worked closely with business teams to understand reporting needs and translated them into SQL queries and Python scripts, ensuring accurate and timely insights delivered 20% faster for strategic planning and decision-making. Designed interactive dashboards in Tableau and Power BI that gave managers real-time visibility into KPIs, improving decision-making speed by 25% across multiple business units. Applied statistical techniques and hypothesis testing to uncover patterns in sales and operational data, helping optimize business strategies and long-term performance while ensuring consistent data-driven decision-making across functional areas. Automated repetitive reporting tasks using Excel (VLOOKUP, Pivot Tables, Power Pivot) and SQL, cutting manual effort and freeing up time for deeper business-driven analysis, thereby improving overall efficiency, accuracy, and productivity within the organization. Partnered with cross-functional teams to simplify complex data sets into clear visual

AI Engineer at Tungsten Automation

August 1, 2024 - November 28, 2025

Designed NLP and predictive analytics models, improving workflow accuracy by 25% and reducing manual processing time by 30%. Integrated ML Ops workflows with Apache Spark and Databricks to streamline data ingestion and enhance the analytics pipeline reliability. Built scalable, cloud-based AI solutions and real-time dashboards to support operations.

Data Scientist at ARAPL

April 1, 2022 - April 1, 2022

Developed classification, regression, and clustering models using Scikit-Learn, TensorFlow, and PyTorch, improving automation processes by 30%. Built ETL pipelines with Apache Spark & Databricks; designed KPI dashboards; deployed ML models.

Data Analyst

July 1, 2020 - July 1, 2020

Worked closely with business teams to understand reporting needs and translate them into SQL queries and Python scripts, delivering insights 20% faster for strategic planning.