onsite
AI/ML Engineer
AI/ML Engineer
As an AI/ML Engineer, you will dive deep into various data types to deliver data-driven insights and leverage GCP services to train and deploy AI/ML models. This role involves acting as a thought leader, driving successful analytics solutions, and contributing to the establishment of a center of excellence within the AI/ML team.
About the role
Overview of Role
As the ideal AI/ML Engineer, you are someone who can do a deep technical dive and communicate effectively with others. You love wrangling messy data into an elegant solution, and helping others understand the power of their data. This role is a chance to have a huge impact on how businesses operate and make decisions on a daily basis.
Responsibilities:
- Dive deep into a wide range of data (tabular, text, image, etc.) to identify pain-points and deliver data-driven insights to our clients.
- Utilize analytical techniques to determine areas of opportunities to help meet business goals.
- Leverage GCP services to train and deploy off-the-shelf (Vertex AI/AutoML/BQML) or custom models to address a client’s business problem.
- Be a thought leader for your team on projects and contribute to key practice initiatives.
- Act as subject matter expert on pre-sales calls and requests for proposals.
- Drive successful delivery of analytics solutions.
- Create reports and presentations that showcase the value of your solution to our clients.
- Work with other members of the AI/ML team to establish a center of excellence and create standard operating procedures, accelerators, and sales assets.
Qualifications:
- 3-6+ years of relevant experience with data science.
- Python (TensorFlow, Keras, SciKit-Learn, PyTorch), SQL, Shell Scripting experience.
- Data Engineering experience in Data Cleansing, ETL/ELT Pipelines, Vector DBs, Relational DBs, NoSQL DBs, Warehouses.
- Generative AI experience in LLMs, Prompt Engineering, Tuning, RAG, LangChain.
- Statistics & Modeling experience with Time-Series, Clustering, Regression, Classification, Recommendation Systems, Deep Learning, Ensemble Modeling, Reinforcement Learning, EDA, Data Visualization, Feature Engineering, Model Evaluation, Responsible AI/MLOps experience with GIT, building CI/CD Pipelines, API Development, Docker, Deployment, Retraining Pipelines, Monitoring, Model Versioning.
- Google Cloud Experience in the following tools: Vertex AI, Document AI, Cloud Run, Cloud Functions, BigQuery, Pub/Sub, Cloud Storage, Kubernetes, Looker, Graph Data Science experience is a plus.
- Ability to communicate complex, technical processes to non-technical business stakeholders.
- Ability to track changing business requirements and deliver quality solutions both independently and with teams of varying skill set.
- A Bachelor’s degree in Computer Science, Computer Engineering, or related or equivalent work experience required.