ML Ops Engineer Job at Miracle Software Systems (Miracle Heights)

ML Ops Engineer

As an MLOps Engineer, you will be responsible for building, maintaining, and opt...

Location

India , Hyderabad

Salary:

Not provided

NStarX

Expiration Date

Until further notice

Requirements

4 to 10 years of experience in MLOps, DevOps, or ML Engineering
Strong proficiency with cloud platforms such as AWS, Azure, or GCP
Experience with containerization and orchestration tools like Docker and Kubernetes
Hands-on experience with ML model deployment, monitoring, and scaling
Proficiency with CI/CD tools such as Jenkins or GitLab CI
Familiarity with data versioning and management tools such as DVC
Strong coding skills in Python with knowledge of ML libraries like TensorFlow or PyTorch
Strong problem-solving skills and ability to work in a collaborative environment
Effective communication skills for cross-functional teamwork

Job Responsibility

Develop and manage infrastructure for end-to-end ML workflows including model training, deployment, monitoring, and maintenance
Implement CI/CD pipelines for ML models and data workflows
Collaborate with cross-functional teams to build scalable and robust ML infrastructure on cloud and on-premises environments
Monitor and optimize model performance and infrastructure to ensure efficient resource usage
Manage data versioning and model versioning across multiple environments
Implement security, governance, and compliance protocols in ML deployment and data pipelines
Support troubleshooting, debugging, and incident management for ML infrastructure issues

What we offer

Competitive compensation
Opportunity to work with a dynamic team on cutting-edge AI and ML solutions
Professional growth and development opportunities

Fulltime

Senior Software Engineer - ML Infrastructure

We build simple yet innovative consumer products and developer APIs that shape h...

Location

United States , San Francisco

Salary:

180000.00 - 270000.00 USD / Year

Plaid

Expiration Date

Until further notice

Requirements

5+ years of industry experience as a software engineer, with strong focus on ML/AI infrastructure or large-scale distributed systems
Hands-on expertise in building and operating ML platforms (e.g., feature stores, data pipelines, training/inference frameworks)
Proven experience delivering reliable and scalable infrastructure in production
Solid understanding of ML Ops concepts and tooling, as well as best practices for observability, security, and reliability
Strong communication skills and ability to collaborate across teams

Job Responsibility

Design and implement large-scale ML infrastructure, including feature stores, pipelines, deployment tooling, and inference systems
Drive the rollout of Plaid’s next-generation feature store to improve reliability and velocity of model development
Help define and evangelize an ML Ops “golden path” for secure, scalable model training, deployment, and monitoring
Ensure operational excellence of ML pipelines and services, including reliability, scalability, performance, and cost efficiency
Collaborate with ML product teams to understand requirements and deliver solutions that accelerate experimentation and iteration
Contribute to technical strategy and architecture discussions within the team
Mentor and support other engineers through code reviews, design discussions, and technical guidance

What we offer

medical, dental, vision, and 401(k)

Fulltime

Senior Software Engineer – ML Model Compliance & Automation

We are seeking a highly skilled and motivated Senior Software Engineer to lead t...

Location

India , Jaipur

Salary:

Not provided

InfoObjects

Expiration Date

Until further notice

Requirements

Experience Required: 3 - 7 yrs
GoLang (preferred)
Python (preferred)
Bash
MLOps Tools: KitOps, MLModelCI, MLflow, ONNX, TensorFlow, PyTorch, Docker
SBOM & Security: Syft, Grype, Trivy, CycloneDX, SPDX
CI/CD: GitHub Actions, GitLab CI, Jenkins, ArgoCD
Infra: Kubernetes, Docker, Helm, Terraform
Cloud: AWS, GCP, Azure (EKS/GKE/ECS preferred)
Version Control: Git, GitOps

Job Responsibility

Model Packaging & Artifact Management: Design and implement workflows for packaging ML models using KitOps, ONNX, MLflow, or TensorFlow SavedModel
Manage model artifact versioning, registries, and reproducibility
Ensure artifact integrity, consistency, and traceability across CI/CD pipelines
Model Profiling & Optimization: Automate model profiling (latency, size, ops) using MLModelCI, TorchServe, or ONNX Runtime
Apply quantization, pruning, and format conversions (e.g., FP32→INT8) for optimization
Embed profiling and optimization checks into CI/CD pipelines to assess deployment readiness
Compliance & SBOM Generation: Develop pipelines to generate and validate SBOMs for ML models
Implement compliance checks for licensing, vulnerabilities, and security using CycloneDX, SPDX, Syft, or Trivy
Validate schema, dependencies, and runtime environments for production readiness
Cloud Integration & Deployment: Automate model registration, endpoint creation, and monitoring setup in AWS/GCP/Azure

Fulltime

Machine Learning Ops Engineer

The Customer AI & Rapid Prototyping department stands at the forefront of digita...

Location

Portugal , Oporto; Lisbon; Funchal; Ponta delgada

Salary:

Not provided

TUI

Expiration Date

Until further notice

Requirements

Experience in productionising and using various AI models and algorithms
Experience in deploying AI solutions using CI/CD pipelines, API development and containers
Strong programming skills in Python
Understanding of machine learning/AI frameworks and libraries
Hands-on experience with cloud technologies and services (e.g., AWS, Azure, Google Cloud)
Experience with monitoring and log collection systems (e.g. DataDog)
Some experience with Generative AI technologies (e.g. Bedrock, Langchain, LangGraph)
Customer-focused engineer with a passion for crafting high-quality digital products, continuous improvement, and effective team collaboration
Strong problem-solving and communication skills, with an understanding of the social, legal, and ethical impact of AI technologies

Job Responsibility

Develop, implement, and maintain machine learning models and algorithms
Work closely with cross-functional teams to integrate ML solutions into production systems
Monitor and optimize the performance of deployed AI models
Collaborate with engineering colleagues on AI-related tasks to deliver impactful, data-driven solutions
Research, evaluate, and test new approaches, processes, and tools

What we offer

Attractive remuneration
bonus opportunity
exclusive travel perks & discounts
extensive health & wellbeing support
Flexible working
hybrid or remote working models
Opportunities to upskill, reskill and grow your career
Access the TUI Tech Learning Hub
Participate in our tech communities and collaborate on global projects and teams
Get involved with incredible local charity and sustainability initiatives like the TUI Care Foundation and the Sustainable Tech Community

Fulltime

Data Infrastructure Engineer

A venture-backed startup at the intersection of AI and national security is buil...

Location

United States , New York City Metropolitan Area

Salary:

Not provided

Orbis Consultants

Expiration Date

Until further notice

Requirements

Strong engineering experience in Python, Go, or C
Experience building and scaling production data systems
Hands-on expertise with model deployment and ML Ops practices
Knowledge of database design, performance tuning, and operations
Someone who thrives in early-stage, fast-paced environments and enjoys tackling complex challenges

Job Responsibility

Build and maintain the data pipelines and infrastructure that power ML applications
Deploy and manage models at scale, from training through production
Design APIs and services that integrate smoothly into mission-critical workflows
Ensure data is handled and secured properly across large, distributed environments
Collaborate closely with a small, fast-moving team to solve hard technical problems in real-world settings

What we offer

Significant equity
Strong health & wellness benefits

Fulltime

Staff Machine Learning Engineer

Machine Learning Engineers at Rocket Money further our mission by building produ...

Location

United States , San Francisco; Washington, D.C.; New York City; Silver Spring; Miami; Denver

Salary:

210000.00 - 260000.00 USD / Year

Truebill

Expiration Date

Until further notice

Requirements

8+ years of professional experience in machine learning engineering or data science roles
Proven track record of designing and implementing ML systems at consumer tech scale and speed
Extensive hands-on experience integrating ML and AI methods into production workflows, including creating evaluation tooling and effective user feedback mechanisms
Experience with prompt engineering and management, creating robust systems for testing and optimizing LLM-based applications
Expert-level proficiency in Python, SQL, and at least a handful of common ML frameworks
Understanding of ML methods at a fundamental level
Master at taking ambiguous problems, creating clarity, and breaking down work into manageable chunks for implementation
Owned the development, launch, and maintenance for several scaled ML/AI powered product experiences
Understand basic software engineering and computer science fundamentals and have applied them at consumer grade scale to build ML powered products in production environments
Technical leader who can identify both emergent technical opportunities and gaps relative to best practice

Job Responsibility

Lead the architecture and development of complex AI and ML powered features across Rocket Money's product suite
Design, implement, and maintain robust evaluation frameworks
Develop novel new product experiences
Own end to end development and implementation of ML and AI product features in collaboration with cross-functional product development teams
Provide technical mentorship

What we offer

Health, Dental & Vision Plans
Competitive Pay
401k Matching
Unlimited PTO
Lunch daily (in-office only)
Snacks & Coffee (in-office only)
Commuter benefits (in-office only)
Bonus

Fulltime

Engineering Manager - Machine Learning Infrastructure

We build simple yet innovative consumer products and developer APIs that shape h...

Location

United States , San Francisco

Salary:

241200.00 - 400000.00 USD / Year

Plaid

Expiration Date

Until further notice

Requirements

8–10 years of experience in ML infrastructure, including direct hands-on expertise as an engineer, IC/TL
2+ years of experience managing infrastructure or ML platform engineers
Proven experience delivering and operating ML or AI infrastructure at scale
Solid technical depth across ML/AI infrastructure domains (e.g., feature stores, pipelines, deployment, inference, observability)
Demonstrated ability to drive execution on complex technical projects with cross-team stakeholders
Strong communication and stakeholder management skills

Job Responsibility

Lead and support the ML Infra team, driving project execution and ensuring delivery on key commitments
Build and launch Plaid’s next-generation feature store to improve reliability and velocity of model development
Define and drive adoption of an ML Ops “golden path” for secure, scalable model training, deployment, and monitoring
Ensure operational excellence of ML pipelines, deployment tooling, and inference systems
Partner with ML product teams to understand requirements and deliver solutions that accelerate model development and iteration
Recruit, mentor, and develop engineers, fostering a collaborative and high-performing team culture

What we offer

medical
dental
vision
401(k)
equity
commission

Fulltime

ML Ops Engineer

The MLOps Engineer will work closely with the Data Science, Analytics, and Data ...

Location

United States

Salary:

127000.00 - 160550.00 USD / Year

Zelis

Expiration Date

Until further notice

Requirements

2–5 years of experience in ML Ops, ML Engineering, or a related role with a focus on production-level model monitoring, automation, and deployment
Strong experience with ML observability tools or custom-built monitoring systems
Experience with monitoring LLMs and Generative AI models, including prompt evaluation, hallucination tracking, and agent behavior auditing
Experience in deploying and managing ML workloads using containerization and orchestration platforms such as Docker, Kubernetes, Kubeflow, or TensorFlow Extended
Familiarity with AutoML pipelines and workflow management tools (e.g., MLflow, SageMaker Autopilot)
Experience working in cloud environments, preferably AWS (e.g., SageMaker, S3, Lambda, ECS/EKS)
Understanding of ML lifecycle tools (e.g., MLflow, SageMaker Pipelines) and CI/CD practices
Strong security and compliance awareness, particularly related to model/data governance (e.g., HIPAA, GDPR)
Proficiency in Python and key data libraries (Pandas, Numpy, Matplotlib, etc.)
Advanced SQL skills and experience with Snowflake or similar data warehousing platforms

Job Responsibility

Build and maintain monitoring infrastructure for conventional machine learning models, with capabilities for performance tracking, drift detection, and alerting
Research, evaluate, and implement monitoring strategies and tools for Generative AI systems, including LLMs and Agentic AI architectures
Collaborate with ML Engineers, Data Scientists, and DevOps teams to deploy, manage, and monitor models in production
Develop and support scalable, secure, and automated data pipelines using Snowflake, SQL, and Python for training, serving, and monitoring ML and GenAI models
Leverage AutoML tools and frameworks (e.g., MLflow, Kubeflow, SageMaker Autopilot) to streamline experimentation and deployment
Design dashboards and reporting systems to visualize model health metrics and surface key operational insights
Ensure auditability, reproducibility, and compliance for model performance and data flow in production environments, with consideration for regulatory standards like GDPR and HIPAA
Maintain CI/CD workflows and version-controlled codebases (e.g., Git) for ML infrastructure and pipelines
Utilize containerization and orchestration technologies (e.g., Docker) to manage scalable ML infrastructure
Leverage tools such as Streamlit and Python visualization libraries to present insights from model and data monitoring

What we offer

401k plan with employer match
flexible paid time off
holidays
parental leaves
life and disability insurance
health benefits including medical, dental, vision, and prescription drug coverage

Fulltime

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