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For one of our clients, we are looking for a Senior Site Reliability Engineer, remotely from Europe.

As a Senior Site Reliability Engineer, you will be responsible for designing, maintaining, and optimizing reliable and scalable systems. You will track performance metrics, improve system reliability through automation, and ensure best practices for incident management. With your expertise in cloud services, container orchestration, and system performance, you will drive initiatives to enhance the efficiency and robustness of the infrastructure while collaborating closely with engineering teams to design systems built for high availability. This is a key role for someone passionate about building and maintaining resilient systems that ensure seamless operations at scale.

Accountabilities:

Tiger Analytics is looking for experienced Machine Learning Engineers with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.

We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world. You will be responsible for:

• Providing solutions for the deployment, execution, validation, monitoring, and improvement of MLE solutions
• Creating Scalable Machine Learning systems .
• Building reusable production data pipelines for implemented machine learning models
• Writing production-quality code and libraries that can be packaged as containers, installed and deployed

You will collaborate with cross-functional teams and business partners and will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.

Requirements

MLE Skillsets needed:

•          Good exposure to Model development and deployment

•          Experience developing API’s

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Various market research firms, including Forrester and Gartner, has recognized our business value and leadership. We are headquartered in Silicon Valley and have our global delivery center in Chennai, India. If you are passionate to work on unstructured business problems that can be solved using data and excited about building, leading, and enabling a team of analytics professionals toward that objective, we would like to talk to you.

Core Responsibilities:

Data Security Analysis:

• Assess current data access policies, security protocols, and data classification procedures.
  

Databricks Component Design:

• Create detailed design of data access control mechanisms within Databricks using appropriate features.
  
  

Collaboration & Documentation:

• Collaborate with the Platform Architect to ensure alignment between data security controls and the overall UAM architecture.
  
• Document the design and implementation of data access control within Databricks.

Requirements

Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best analytics global consulting team in the world.

We are seeking an experienced Data Engineer to join our team, specifically focused on building scalable Generative AI architectures within the AWS ecosystem. You will architect the data foundations that power LLMs and autonomous agents for our Fortune 500 partners.

Requirements

• Experience: 8-12 years in Data Engineering with a heavy focus on the AWS Cloud stack.

• AWS Expertise: Deep hands-on experience with Glue, Athena, EMR, and Redshift.

• AI/ML Tools: Proficiency in LangChain or LlamaIndex integrated with AWS services to handle unstructured data (text, images, PDFs).

• DevOps & IAC: Experience deploying infrastructure using AWS CDK or Terraform.

• Core Skills: Advanced SQL, Python and PySpark skills tailored for distributed processing on AWS.

Benefits