Machine Learning Engineer

Job Summary

We are seeking a dynamic and innovative Machine Learning Engineer to join our cutting-edge data science team. In this role, you will harness the power of artificial intelligence and machine learning frameworks to develop, train, and deploy sophisticated models that drive strategic decision-making and enhance product offerings. Your expertise in big data technologies, natural language processing, and model deployment will be pivotal in transforming complex datasets into actionable insights. This position offers an exciting opportunity to work with a diverse set of tools and technologies, including cloud platforms, big data ecosystems, and advanced analytics, to shape the future of intelligent solutions.

Duties

• Design, develop, and optimize machine learning models utilizing frameworks such as TensorFlow, R, and Spark to solve complex business problems.
• Lead end-to-end model training processes, from data preprocessing and feature engineering to validation and fine-tuning for accuracy and efficiency.
• Implement unsupervised learning techniques for clustering, anomaly detection, and data mining to uncover hidden patterns within large datasets.
• Deploy machine learning models into production environments using cloud services like AWS, ensuring scalability and robustness.
• Collaborate with data engineers to develop ETL pipelines using Talend, Bash scripts, and SQL for seamless data ingestion from diverse sources such as Hadoop clusters and linked data repositories.
• Design and maintain databases with optimized schema structures to support high-performance analytics applications.
• Conduct natural language processing (NLP) tasks to analyze text data for sentiment analysis, chatbots, or document classification.
• Utilize big data tools such as Hadoop, Spark, and SQL for efficient data processing and analytics.
• Apply advanced analytics techniques to extract insights from structured and unstructured data sources.
• Stay abreast of emerging AI research including quantum engineering principles that can be integrated into future projects.
• Develop dashboards with Looker or similar BI tools to visualize model outputs and key metrics for stakeholders.
• Document processes thoroughly for reproducibility and knowledge sharing across teams.

Skills

• Strong proficiency in Python, R, Java, C, and VBA for developing machine learning algorithms and automation scripts.
• Extensive experience with machine learning frameworks such as TensorFlow, SAS, Spark MLlib, or equivalent platforms.
• Expertise in AWS cloud services including EC2, S3, SageMaker for scalable model training and deployment.
• Deep understanding of big data ecosystems like Hadoop and Spark for large-scale data processing.
• Proven ability in designing efficient database schemas using SQL or NoSQL databases; experience with database design principles is essential.
• Skilled in ETL tools such as Talend or custom Bash scripts for data integration workflows.
• Knowledge of natural language processing techniques for text analysis applications.
• Familiarity with linked data concepts and semantic web technologies to connect disparate datasets effectively.
• Experience working with analytics platforms like Looker or similar BI tools for reporting insights visually.
• Ability to implement unsupervised learning algorithms such as clustering or dimensionality reduction methods.
• Strong understanding of model training procedures including hyperparameter tuning and validation strategies.
• Knowledge of quantum engineering principles that could influence future AI research initiatives is a plus. Join us if you're passionate about leveraging the latest in AI technology to solve real-world problems We value innovation-driven minds eager to push the boundaries of what's possible with machine learning—your expertise will help shape the future of intelligent solutions across industries

Job Type: Full-time

Pay: $77,246.83-$159,239.61 per year