Machine Learning Engineer

Job Summary

Roles and Responsibilities

• Build outstanding domain-focused data solutions with internal teams, business analysts, and stakeholders.
• Apply AI/ML practices and standards to develop robust and maintainable solutions.
• Motivated by a fast-paced, service-oriented environment and interacting directly with clients on new features for future product releases.
• A natural problem-solver and intellectually curious across a breadth of industries and topics.
• Acquainted in different aspects of Data Management like Data Strategy, Architecture, Governance, Data Quality, Integrity Data Integration, and Model Deployment.
• Study and transform data science prototypes.
• Extremely well-versed in designing/developing models and monitoring.

Who Fits Best

• You are a data enthusiast and problem solver.
• You are a self-motivated and fast learner with a strong sense of ownership and drive.
• You enjoy working in a fast-paced creative environment.
• You appreciate great design, have a strong sense of aesthetics and have a keen eye for detail.
• You thrive in a customer-centric environment with the ability to actively listen, empathize and collaborate with globally distributed teams.
• You are a team player who desires to mentor and inspire others to do their best.
• You love expressing ideas and articulating well with strong written and verbal English communication and presentation skills.
• You are detail-oriented with an appreciation for craftsmanship.

Qualifications and Skills

• Bachelor's degree in Computer Science, Information Technology, or allied streams.
• 3+ years of hands-on experience in the data engineering domain with data science development.
• Must have experience with end-to-end data science project implementation on Azure or GCP.
• Must have Python, TensorFlow, and Keras for implementing complex models and end-to-end pipelines.
• Good with Matplotlib/Seaborn for creating good data visualizations for interpreting data.
• Good with Pandas and NumPy for data-wrangling tasks.
• Solid understanding of DS concepts such as Feature Engineering, Model development, model deployment, model monitoring, hyperparameter tuning.
• Expertise in TensorFlow - Model Building, Feature Engineering, Model Deployment, and Monitoring.
• Understanding of Apache Spark, Airflow, Hudi, Iceberg, Nessie, NiFi, Luigi, and Arrow (Good to have).
• Strong foundations in computer science, data structures, algorithms, and programming logic.
• Excellent logical reasoning and data interpretation capability.
• Ability to interpret business requirements accurately.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.