▷ [Only 24h Left] Senior Consultant - Machine Learning Engineering

Responsibilities:

Description

% of Time Spent

· Data Acquisition: Work with Data Engineering team to understand and help to develop build-as-per-need infrastructure for Data collection and ETL processes, automate steps in ETL & develop system to manage, deploy and maintain Data Engineering code. Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader. Work with data and analytics experts to strive for greater functionality in our data systems (including feature engineering).

· Model orchestration & deployment: Assist in the development of systems to manage, deploy and maintain ML code. Work closely with the Data Sciences team to: Develop infrastructure in order for Machine Learning models to be deployed, Take over newly developed models into production, Develop systems for integrating AI/ML components using orchestration services. Build CI-CD pipelines interconnecting Data services and ML services for the project with an aim to achieve MLOps. Assist in development and implementation of ML toolchains and data platforms to scale ML solutions in production.

· Governance and operational support: Enable the agility in data science delivery through automation across build, validation, deployment and monitoring of Data Science models. Monitor quality parameters for ML models in production. Shape and operate best practices for managing models in production. Contribute to solutions that accelerate the task of Production issue analysis by Data Scientists by enabling log viewing tracing and debugging of data science features in production.

Qualifications
Describes the minimum education and experience, certifications, licenses, physical demands, working conditions and skill sets needed to perform the job.

Provide prompt, courteous and excellent service at an acceptable cost to all customers; operate in an ethical manner in accordance with all applicable laws and regulations, the company's Corporate Code of Ethics, employee handbook, applicable compliance and operations policies and procedures, and other policies of the company. Possess a high degree of integrity and actively cooperate and interact with all entities of the Principal Financial Group.

· Bachelor’s Degree in Computer Science/Engineering, Informatics, or a related technical discipline"

· 6-8 years of experience in below mentioned tools/technology

· Proficiency in orchestration of machine learning services with tools like Kubernetes or Kubeflow

· Proficiency in streamlining and automating data ingestion process, building data pipelines and deploying machine learning models

· Proficiency with machine learning frameworks (like Keras, PyTorch, pyspark) and libraries (like scikit-learn)

· Proficient working on data solutions with big data and cloud technology like Azure/AWS: Redshift, RDS, S3, Glue, Athena, EMR, Spark, Hive, etc.)

· Proficiency in object-oriented/object function scripting languages: Python, R, shell scripting, Java, C++, Scala, etc

· Cloud computing proficiency (AWS and Azure preferred)

As part of AI COE, T6 - Leader needs to manage the team for LLM Ops, CI/CD requirements, orchestration and deployment, governance and operational support to provide support during PGS working hours

Qualifications:

- Bachelor's Degree + 10-12 years analytics, consulting, project management, or equivalent experience preferred
- Applies advanced knowledge of job area typically obtained through advanced education and work experience.
- Managing projects / processes, working independently with limited supervision.
- Coaching and reviewing the work of lower level professionals.
- Problems faced are difficult and sometimes complex.