MLOps Engineer Job at Bright Vision Technologies (Bridgewater)

Mlops Engineer

Location

Australia , Sydney

Salary:

Not provided

AKUNA CAPITAL

Expiration Date

Until further notice

Requirements

Bachelor's degree or higher in Computer Science, Engineering or a related technical field
Minimum 3+ years full-time experience building, deploying, or operating machine learning infrastructure in production environments
Hands-on experience with ML infrastructure or data platforms such as Databricks or Spark
Strong programming skills in Python, C++, or both in Linux-based environments
Effective communication skills, with the ability to partner effectively across engineering, research, and business teams
Demonstrated ownership, technical leadership, and ability to define and execute a roadmap

Job Responsibility

Design, own and maintain the machine learning infrastructure, partnering with cross functional teams across the lifecycle of key ML initiatives
Own and drive the roadmap for Akuna’s machine learning infrastructure, tooling, and processes
Take a hands-on role designing, building, and maintaining platforms that enable efficient model development, training, deployment, monitoring, and governance
Establish best practices for reproducible ML workflows, model lifecycle management, CI/CD, observability, and production reliability
Operate and continuously improve ML infrastructure to ensure it is scalable, performant, reliable, and easy for researchers and engineers to use
Provide technical leadership and guidance to engineering and research teams adopting ML infrastructure capabilities

Fulltime

Mlops Engineer

Akuna Capital is an innovative trading firm with a strong focus on collaboration...

Location

Singapore , Singapore

Salary:

Not provided

AKUNA CAPITAL

Expiration Date

Until further notice

Requirements

Bachelor’s degree or higher in Computer Science, Engineering or a related technical field
Minimum 3+ years full-time experience building, deploying, or operating machine learning infrastructure in production environments
Hands-on experience with ML infrastructure or data platforms such as Databricks or Spark
Strong programming skills in Python, C++, or both in Linux-based environments
Effective communication skills, with the ability to partner effectively across engineering, research, and business teams
Demonstrated ownership, technical leadership, and ability to define and execute a roadmap

Job Responsibility

Design, own and maintain the machine learning infrastructure, partnering with cross functional teams across the lifecycle of key ML initiatives
Own and drive the roadmap for Akuna’s machine learning infrastructure, tooling, and processes
Take a hands-on role designing, building, and maintaining platforms that enable efficient model development, training, deployment, monitoring, and governance
Establish best practices for reproducible ML workflows, model lifecycle management, CI/CD, observability, and production reliability
Operate and continuously improve ML infrastructure to ensure it is scalable, performant, reliable, and easy for researchers and engineers to use
Provide technical leadership and guidance to engineering and research teams adopting ML infrastructure capabilities

Fulltime

MLOps Engineer

The Senior Associate Software Development Engineer is a developing subject matte...

Location

India , New Delhi

Salary:

Not provided

NTT DATA

Expiration Date

Until further notice

Requirements

Developing understanding of cloud architecture and services in multiple public clouds like AWS, GCP, Microsoft Azure, and Microsoft Office 365
Subject matter expert in programming languages such as C/C++, C#, Java, JavaScript, Python, Node.js, libraries and frameworks
Developing expertise of data structures, algorithms, and software design with strong analytical and debugging skills
Developing knowledge of micro services-based software architecture and experience with API product development
Developing expertise in SQL and no-SQL data stores including Elasticsearch, MongoDB, Cassandra
Developing understanding of container run time (Kubernetes, Docker, LXC/LXD)
Developing proficiency with agile, lean practices and believes in test-driven development
Possess a can-do attitude and one that takes initiative
Excellent ability to work well in a diverse team with different backgrounds and experience levels
Excellent ability to thrive in a dynamic, fast-paced environment

Job Responsibility

Designs and develops solutions and functionality that drives the growth of business
Contributes to writing and testing code
Supports the execution of automated testing
Participates in software deployment
Supports the delivery of software components while working in collaboration with the product team
Supports the integration and building of solutions through automation and coding, using 3rd party software
Crafts, builds, and debug large scale distributed systems
Writes, updates, and maintains the technical program, end-user documentation, and operational procedures
Assists with refactoring code
Contributes to the reviewing of code written by other developers

Fulltime

Mlops Engineer

NTT DATA strives to hire exceptional, innovative and passionate individuals who ...

Location

United States , Plano

Salary:

Not provided

NTT DATA

Expiration Date

Until further notice

Requirements

8+ Years experience with: MLOps Azure Kubernetes Argo / Bento Azure ML Studio Model Inferencing

Job Responsibility

Exercise expertise in ideating and developing ML applications on prediction, recommendation, text analytics, computer vision, bots, and document intelligence
Demonstrate deep knowledge of ML frameworks such as TensorFlow, PyTorch, Keras, Spacy, and scikit-learn
Employ technical knowledge and hands-on experience with Azure ML Studio and Azure Kubernetes Service
Experience in deploying Azure cloud services using Terraform templates with strong knowledge of DevOps principles and automated deployments
Leverage advanced knowledge of Python open-source software stack such as Django or Flask, Django Rest or FastAPI, etc.
Work on model inferencing, validation and deployments to ensure models are deployed with the appropriate levels of validation and quality
Create and maintain infrastructure to ingest, normalize, and combine datasets for actionable insights
Interact at appropriate levels to ensure client satisfaction and project success
Communicate complex technical concepts clearly to non-technical audiences

Fulltime

MLOps Engineer

We are looking for a proactive MLOps Engineer to join our staff data engineer an...

Location

Spain

Salary:

Not provided

Bark

Expiration Date

Until further notice

Requirements

Experience deploying and maintaining Python services in a major cloud environment (AWS, GCP, Azure)
Specific experience with the AWS stack, including Kinesis, Lambdas, Glue, Firehose, and Athena
Experience with MLOps frameworks and experiment tracking tools such as AWS Sagemaker, MLFlow, Databricks, or W&B
Basic knowledge of ML Inference REST APIs (FastAPI)
Great skills improving and operating Schema Registries and Data Catalogs (Glue, Databricks, etc.)
Relevant CI/CD experience (e.g., GitHub Actions, Gitlab Pipelines) automating tests and updates in schema registries and lambda releases
Solid experience with SQL and data warehousing, data lake environments (e.g. DataBricks, BigQuery, Redshift, S3)
Familiarity with cloud observability tools (e.g. Datadog, NewRelic, or Cloudwatch)

Job Responsibility

Build and operate a scalable data platform ingesting real-time events with a high-throughput rate
Collaborate with Data Scientists to transition ML models from experimentation to production
Build and maintain ML infrastructure for model serving (using FastAPI) and track model performance and lifecycle over time
Collaborate with analysts, engineers and product managers to understand user needs and take ownership of producing new event tracking functionality
Implement automations, high data quality controls, ensure data integrity in the ingested data, and create necessary monitoring alerts

Fulltime

MLOps Engineer

We are seeking an experienced MLOps Engineer to design, deploy, monitor, and mai...

Location

United States , Houston

Salary:

Not provided

Robert Half

Expiration Date

Until further notice

Requirements

Master’s degree or higher (PhD preferred) in Computer Science, Engineering, or related discipline
5+ years of relevant experience in MLOps, ML engineering, platform engineering, or DevOps
Strong hands-on experience with AWS, Microsoft Azure, and Snowflake
Proficiency in Python and SQL
Proven experience deploying and managing ML models in production environments
Experience with AWS SageMaker and Azure Machine Learning
Experience building and integrating data pipelines with Snowflake
Strong understanding of CI/CD pipelines, infrastructure automation, and model versioning
Experience with containers and orchestration tools such as Docker and Kubernetes
Experience with Airflow, Azure Data Factory, or similar workflow orchestrators

Job Responsibility

Design and implement end-to-end ML pipelines for ingestion, feature engineering, training, validation, deployment, and monitoring
Deploy and manage ML models in production across AWS, Azure, and Snowflake ecosystems
Build batch and real-time inference pipelines using cloud-native and platform-native services
Automate model packaging, testing, releases, and rollback using CI/CD best practices
Integrate ML workflows with AWS SageMaker, AWS Lambda, Azure Machine Learning, Azure Data Factory, and Snowflake
Build and maintain orchestration workflows using Airflow, Azure Data Factory, or similar tools
Implement experiment tracking, model registries, and model governance processes
Monitor model accuracy, drift, latency, throughput, pipeline performance, and infrastructure usage
Establish advanced deployment strategies (canary, shadow, blue-green, rollback)
Collaborate with cross-functional teams to transition models from research to production

What we offer

medical
vision
dental
life and disability insurance
401(k) plan

MLOPS Engineer

Join our team and help build the machine learning production infrastructure for ...

Location

Salary:

Not provided

Cogniphi

Expiration Date

Until further notice

Requirements

Over 3 years of experience building production-quality software
Experience building end-to-end systems as a Platform Engineer, ML DevOps Engineer, or Data Engineer (or equivalent)
Strong software engineering skills in complex, multi-language systems
Fluency in Python
Comfort with Linux administration
Experience working with cloud computing and database systems
Experience building custom integrations between cloud-based systems using APIs
Experience developing and maintaining ML systems built with open source tools
Experience developing with containers and Kubernetes in cloud computing environments
Familiarity with one or more data-oriented workflow orchestration frameworks (KubeFlow, Airflow, Argo, etc. – Kubeflow is a must and the ability to understand each framework and select the best tool for need is a must)

Job Responsibility

Designing data pipelines and engineering infrastructure to support clients’ enterprise machine learning systems at scale
Taking offline models from data scientists and turning them into a real machine learning production system
Developing and deploying scalable tools and services for clients to handle machine learning training and inference
Identifying and evaluating new technologies to improve the performance, maintainability, and reliability of clients’ machine learning systems
Applying software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.
Supporting model development, with an emphasis on auditability, versioning, and data security
Facilitating the development and deployment of proof-of-concept machine learning systems
Communicating with clients to build requirements and track progress

What we offer

Niche projects in Computer Vision, AI, and Telematics in multiple industry sectors
Platform and product implementations
Tier -1 technology partners and supportive management ensure individual as well as overall company growth
Global Work Culture
Psychological Safe Workplace

MLops Engineer

We are seeking an experienced MLOps Engineer with deep expertise in cloud servic...

Location

United States

Salary:

Not provided

Velvetech

Expiration Date

Until further notice

Requirements

MLOps expertise: End-to-end ML pipelines (Azure ML, AWS SageMaker, MLflow), Docker, Kubernetes, CI/CD for ML.
LLMOps experience: Deploying open-source LLMs (Llama, Mistral, R1), optimizing LLM inference, RAG, fine-tuning.
Software engineering: Python, ML frameworks (PyTorch, TensorFlow), microservices, data pipelines.
Problem-solving: Evaluating and fine-tuning ML/LLM models, tracking metrics, optimizing AI solutions.

Job Responsibility

MLOps and ML Lifecycle Management: Develop and optimize MLOps pipelines for scalable model development and deployment.Automate model training, deployment, monitoring, and testing workflows.Manage data pipelines, ensuring efficient training data preparation.Implement model performance tracking and versioning using MLflow
LLMOps and Large-Scale AI Deployments: Deploy and fine-tune open-source LLM models for various business use cases. Utilize vLLM, LiteLLM, BentoML, Ollama for optimized LLM inference and deployment.Monitor and evaluate LLM performance across different metrics including latency, accuracy, and cost-effectiveness
AI Solutions for Marketplace Optimization:Develop AI-based solutions for product category classification and product data enrichment. Implement dynamic price optimization models and forecast price and demand trends. Build AI systems to select optimal recommerce channels for selling products, based various business factors, including price seasonality and inventory costs.

What we offer

Velvetech is in the TOP 5 development companies in Illinois, USA
You have FLEXIBLE working conditions and a COOPERATIVE environment
Competitive salary
Many CHALLENGING and exciting projects with new opportunities and learning
GROWTH opportunities, skills and competencies improvement, and professional certification
In-company TRAINING (English, Software / DevOps / Project management / Design / Business)

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