Design, implement, and own end-to-end scalable ML systems and MLOps lifecycle (deployment, monitoring, metrics). Optimize models and system performance, work with Java/Python and TF/PyTorch, use CI/CD, Terraform, Docker/Kubernetes, lead inter-team communication, document work, and meet deadlines.
Greetings Everyone
Who are we?
For the past 20 years, we have powered many Digital Experiences for the Fortune 500. Since 1999, we have grown from a few people to more than 4000 team members across the globe that are engaged in various Digital Modernization. For a brief 1 minute video about us, you can check https://youtu.be/uJWBWQZEA6o.
Must Have - Tech Skills:
1. Hands on with designing end to end scalable ML system (should have worked on recent projects within last 12 months).
2. Hands on with implementation of scalable ML system. Proven ownership across entire or partial ML and MLOps lifecycle:
a. Evaluation Techniques.
b. Machine Learning Algorithms.
c. Statistical Modeling.
d. End to end deployment.
e. Metric generation.
f. Model monitoring and deployment.
g. Prompt Engineering,
3. Hand on with ML Model optimization - quantization, pruning, or speculative decoding etc.
4. Hand on with ML Model system optimizations ie ability to quickly identify bottlenecks and resolve them from System perspective.
5. Programming & Frameworks: Hands on and have worked on recent projects (within last 12months) in:
a. Java
i. library/dependency management
ii. Package and distribution management
iii. Algorithms
b. Python
c. Tensorflow / PyTorch
6. Knowledge of DevOps principles and tools (e.g., CI/CD pipelines, Terraform).
7. Strong understanding of containerization technologies (e.g., Docker, Kubernetes).
2. Hands on with implementation of scalable ML system. Proven ownership across entire or partial ML and MLOps lifecycle:
a. Evaluation Techniques.
b. Machine Learning Algorithms.
c. Statistical Modeling.
d. End to end deployment.
e. Metric generation.
f. Model monitoring and deployment.
g. Prompt Engineering,
3. Hand on with ML Model optimization - quantization, pruning, or speculative decoding etc.
4. Hand on with ML Model system optimizations ie ability to quickly identify bottlenecks and resolve them from System perspective.
5. Programming & Frameworks: Hands on and have worked on recent projects (within last 12months) in:
a. Java
i. library/dependency management
ii. Package and distribution management
iii. Algorithms
b. Python
c. Tensorflow / PyTorch
6. Knowledge of DevOps principles and tools (e.g., CI/CD pipelines, Terraform).
7. Strong understanding of containerization technologies (e.g., Docker, Kubernetes).
Must Have - Soft Skills:
1. Good Team worker & good collaborations skills.
2. Ability to abstract out details, define problem & have clear technical communication.
3. Ability to lead inter team communication.
4. Ability to write crisp and effective documentation.
5. Ensures that deadlines are met.
2. Ability to abstract out details, define problem & have clear technical communication.
3. Ability to lead inter team communication.
4. Ability to write crisp and effective documentation.
5. Ensures that deadlines are met.
Good To Have - Tech Skills:
1. GCP ML Tech stack.
2. Experienced with Infrastructure as Code (IaC).
3. Experience with big data technologies such as Apache Spark or Hadoop.
4. Stay informed about the ethical implications of machine learning eg: selection bias.
5. Model Training
2. Experienced with Infrastructure as Code (IaC).
3. Experience with big data technologies such as Apache Spark or Hadoop.
4. Stay informed about the ethical implications of machine learning eg: selection bias.
5. Model Training
6. Data Analytics - figure out anomalies , skew , discrepancies
7. Hands on with developing on device ML System.
7. Hands on with developing on device ML System.
Good To Have - Soft Skills:
1. Mentoring and Leadership.
2. Project Management.
Compensation, Benefits and Duration
Minimum Compensation: USD 51,000
Maximum Compensation: USD 178,000
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full-time employees.
This position is available for independent contractors
No applications will be considered if received more than 120 days after the date of this post
Similar Jobs
eCommerce • Healthtech • Kids + Family • Retail • Social Media
Own Babylist’s global compensation strategy, including executive compensation, equity programs, job architecture, market pricing, pay equity, incentives, and annual compensation cycles. Lead compensation analytics, governance, compliance, budgeting, and executive committee materials. Partner with Finance, Legal, Payroll, HR, and business leaders while advising on pay decisions and workforce planning. Build and develop the compensation team, communicate programs company-wide, and redesign equity strategy as the company prepares for potential IPO growth.
Top Skills:
AIChatgptClaude
Fintech
Supports venture capital clients by ingesting, transforming, mapping, and verifying portfolio financial data from Excel, PDFs, CSVs, and other sources. Improves AI agent workflows, prompt design, and automation protocols while collaborating with Customer Success, Product Support, engineering, product, and operations. Provides customer support and helps scale accurate, efficient data-processing workflows.
Top Skills:
AIExcelGoogle SheetsLlms
Big Data • Fintech • Mobile • Payments • Financial Services
Staff Software Engineer responsible for technical strategy, architecture, and development of web and mobile authentication experiences. Leads major technical initiatives, partners with product, design, and analytics, improves reliability and operational readiness, establishes engineering standards, and mentors team members. Requires extensive experience building web applications with React or Vue, proficiency in JavaScript or TypeScript, strong system architecture and communication skills, and a related degree or equivalent experience.
Top Skills:
JavaScriptReactTypescriptVue
What you need to know about the Austin Tech Scene
Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.
Key Facts About Austin Tech
- Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
- Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
- Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
- Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center
