Position Description
The AIML Platform team is seeking talented senior to principal-level engineers to join our team with a focus on building a machine learning platform to support Machine Learning Development Lifecycle. You will have the opportunity to design and implement solutions such as model-inferencing/model-serving solutions for various data science models including LLMs, Infrastructure as code solutions, as well as designing/implementing alternatives to legacy cloud services and infrastructure. An ideal candidate for this role is an initiative-taker able and willing to support multiple initiatives simultaneously, intellectually curious and thrives in an environment with constantly shifting priorities that require learning about latest developments in machine learning from a platform perspective.
Responsibilities
As a Senior or Principal Engineer, you will:
- Scope, design, and build systems with high scalability, reliability, and resilience
- Support platform initiatives geared toward model deployment, serving, inferencing, and/or monitoring solutions
- Research and implement variety of cloud and/or open-source tools and services across the Model development life cycle ranging from IaC (Infrastructure as code) to self-hosted infrastructure implementation.
- Engage with partner teams to debug production issues, pipeline failures, and system latencies
- Engage in cross-functional collaboration with teams of developers, data scientists, product managers, network and security, and other areas throughout the entire MDLC lifecycle
- Lead in design sessions and code reviews with peers
- Mentor other engineers
- Consistently share best practices and improve processes within and across teams
Qualifications
Required
- Minimum 6 years of technology experience with a focus on developing scalable and reliable software systems and/or applications
- Proficiency in programming languages such as Python or Java (at least one is required, ideally python)
- Proficiency in designing and implementing scalable and reliable systems/platforms
- Experience with containerization technologies such as Docker and container orchestration platforms like Kubernetes
- Experience onboarding, implementing open-source solutions in existing / new workflows.
- Experience with Dev-ops practices and tools for building and deploying production grade code
- Experience with CI/CD pipelines using YAML
- Experience Monitoring pipelines for failures and diagnosing/resolving problems
- Experience with version control systems such as git
- Experience with Cloud Platforms such as Azure, AWS, and Google Cloud
- Working knowledge of networking concepts (DNS/DHCP/Firewalls/Sub-netting, etc.)
- Knowledge of Big Data platforms such as Snowflake, ADLS, Databricks, Cosmos DB
- Knowledge of Big Data processing frameworks and languages such as Spark, Scala
- Excellent communication and analytical skills, and proven problem-solving ability
Desired
- Experience with machine learning model serving frameworks and machine learning platforms such as Jupyter notebooks, MLFlow, Azure Machine Learning etc.
- Experience with at least one IaC (Infrastructure as code) provider, preferably Terraform
- Experience with implementing monitoring and alerting systems to ensure performance and reliability of deployed models
- Experience with infrastructure optimization for cost efficiency, scalability, and reliability
- Experience with MLOps practices such as model versioning, model monitoring, and model governance
- Knowledge of microservice architecture and distributed systems
- Experience performing Root Cause Analysis (RCA) for application and infrastructure related issues
Experience
- 1+ years of professional software development/DevOps/Cloud engineering experience with Python, Java and/or other programming languages
- 2+ years of experience with system design
- 2+ years of experience in open-source frameworks
- 4+ years of experience with AWS, GCP, Azure, or another cloud service
Annual Salary
$130,000.00 - $260,000.00The above annual salary range is a general guideline. Multiple factors are taken into consideration to arrive at the final hourly rate/ annual salary to be offered to the selected candidate. Factors include, but are not limited to, the scope and responsibilities of the role, the selected candidate’s work experience, education and training, the work location as well as market and business considerations.
Benefits:
As an Associate, you’ll enjoy our Total Rewards Program* to help secure your financial future and preserve your health and well-being, including:
- Premier Medical, Dental and Vision Insurance with no waiting period**
- Paid Vacation, Sick and Parental Leave
- 401(k) Plan
- Tuition Reimbursement
- Paid Training and Licensures
*Benefits may be different by location. Benefit eligibility requirements vary and may include length of service.
**Coverage begins on the date of hire. Must enroll in New Hire Benefits within 30 days of the date of hire for coverage to take effect.
The equal employment opportunity policy of the GEICO Companies provides for a fair and equal employment opportunity for all associates and job applicants regardless of race, color, religious creed, national origin, ancestry, age, gender, pregnancy, sexual orientation, gender identity, marital status, familial status, disability or genetic information, in compliance with applicable federal, state and local law. GEICO hires and promotes individuals solely on the basis of their qualifications for the job to be filled.
GEICO reasonably accommodates qualified individuals with disabilities to enable them to receive equal employment opportunity and/or perform the essential functions of the job, unless the accommodation would impose an undue hardship to the Company. This applies to all applicants and associates. GEICO also provides a work environment in which each associate is able to be productive and work to the best of their ability. We do not condone or tolerate an atmosphere of intimidation or harassment. We expect and require the cooperation of all associates in maintaining an atmosphere free from discrimination and harassment with mutual respect by and for all associates and applicants.
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