Software Engineering, Machine Learning Job at Meta

Software Engineering, Machine Learning

Meta is seeking talented engineers to join our teams in building cutting-edge pr...

Location

India , Hyderabad

Salary:

Not provided

Software engineering & machine learning intern

We’re looking for early-career engineers who want to learn fast, work with exper...

Location

France , Paris

Salary:

Not provided

VO2 Group

Expiration Date

Until further notice

Requirements

Currently pursuing or recently graduated in Computer Science, Engineering, Applied Math, or a related field
Comfortable coding in at least one: Java, Kotlin, Python, or TypeScript
Passionate about AI, data, or building meaningful product features
Curious, collaborative, and excited to learn
Humble and resilient — you ask questions, take feedback, and grow

Job Responsibility

Contribute to real features and products
Work across multiple domains: Apps: Web app, frontend logic, UI/UX
Platform: Backend services, infrastructure, APIs
Core (ML): Algorithms, models, data systems

What we offer

Real Impact from Day One
Learning Everywhere
Lean, Ambitious Team
Healthcare Mission
Career Launchpad
Flexible working hours
Team building
100% covered health insurance
Sustainable mobility package
Employee stock purchase plan / BSPCE / Stock options

Fulltime

Machine Learning Software Engineering Manager

Meta is seeking a highly motivated and experienced Software Engineering Manager ...

Location

United States , Sunnyvale

Salary:

219000.00 - 301000.00 USD / Year

Software Engineering Lead, Machine Learning

Ema is building the next generation AI technology to empower every employee in t...

Location

United States , San Francisco Bay Area

Salary:

135000.00 - 300000.00 USD / Year

Ema

Expiration Date

Until further notice

Requirements

Master’s degree or Ph.D. in Computer Science, Machine Learning, or a related quantitative field
Proven industry experience in building and deploying production-level machine learning models
Deep understanding and practical experience with NLP techniques and frameworks, including training and inference of large language models
Deep understanding of any of retrieval, ranking, reinforcement learning, and agent-based systems and experience in how to build them for large systems
Proficiency in Python and experience with ML libraries such as TensorFlow or PyTorch
Excellent skills in data processing (SQL, ETL, data warehousing) and experience working with large-scale data systems
Experience with machine learning model lifecycle management tools, and an understanding of MLOps principles and best practices
Familiarity with cloud platforms like GCP or Azure
Familiarity with the latest industry and academic trends in machine learning and AI, and the ability to apply this knowledge to practical projects
Good understanding of software development principles, data structures, and algorithms

Job Responsibility

Conceptualize, develop, and deploy machine learning models that underpin our NLP, retrieval, ranking, reasoning, dialog and code-generation systems
Implement advanced machine learning algorithms, such as Transformer-based models, reinforcement learning, ensemble learning, and agent-based systems to continually improve the performance of our AI systems
Lead the processing and analysis of large, complex datasets (structured, semi-structured, and unstructured), and use your findings to inform the development of our models
Work across the complete lifecycle of ML model development, including problem definition, data exploration, feature engineering, model training, validation, and deployment
Implement A/B testing and other statistical methods to validate the effectiveness of models. Ensure the integrity and robustness of ML solutions by developing automated testing and validation processes
Clearly communicate the technical workings and benefits of ML models to both technical and non-technical stakeholders, facilitating understanding and adoption

Fulltime

Software Engineering Manager, Machine Learning

Meta is seeking a highly motivated and experienced Software Engineering Manager ...

Location

United States , Sunnyvale

Salary:

184000.00 - 257000.00 USD / Year

New

Machine Learning Software Engineer

In this role, you will design, build, and optimize robust ML models, data pipeli...

Location

Canada , Calgary

Salary:

Not provided

Randstad

Expiration Date

August 08, 2026

Requirements

BSc. or MSc. degree in Computer Science, Engineering, Mathematics, Physics, Statistics, or an equivalent quantitative discipline
Minimum of 3+ years of professional experience successfully delivering AI/ML projects
Minimum of 2+ years operating explicitly as a software developer within a structured delivery team
Mastery of ML algorithms, techniques, and Agentic frameworks, with the proven ability to optimize models with minimal supervision
Advanced expertise in at least two common development languages (e.g., Python, Java, C#)
Proficient working knowledge of general Python data packages and relational/non-relational databases and query engines (e.g., SQL)
Strong foundational knowledge of DevOps automation practices and building production solutions within AWS
Proficient with statistical concepts and capable of applying rigorous statistical thinking to solve complex business problems

Job Responsibility

Build, optimize, and scale machine learning models and end-to-end data pipelines
Design and implement critical operational aspects of model deployment, including automation pipelines, continuous monitoring, and automated drift detection
Transition experimental models and prototypes into robust, maintainable, and production-grade software applications
Participate in research experiments and rapid prototyping to validate next-generation AI concepts
Provide core software engineering expertise to internal data analytics and data science delivery teams
Apply strict software development best practices, including Test-Driven Development (TDD) and automated CI/CD workflows
Review requirements, map system dependencies, and provide accurate implementation effort estimations during team planning sessions
Test, debug, and optimize application code to eliminate performance bottlenecks
Conduct thorough code reviews and provide constructive feedback to elevate overall team code quality
Collaborate closely with architects, data scientists, product teams, and business stakeholders to translate high-level goals into functional ML architectures

What we offer

Cutting-Edge AI Scope: Direct involvement in building and optimizing both traditional ML models and next-generation Agentic solutions with a high degree of autonomy
End-to-End Technical Ownership: Lead the operational deployment (MLOps) of AI models, directly influencing infrastructure automation, model tracking, and system performance
Cross-Functional Collaboration: Serve as the technical software anchor within a diverse ecosystem of data scientists, enterprise architects, and product managers
Modern Cloud Stack: Deepen your expertise in cloud-native deployment using AWS, enterprise data pipelines, and advanced platforms like Databricks

Software Machine Learning Engineer

As a Machine Learning Engineer, you will design, develop, and deploy applied AI ...

Location

United States , North Reading

Salary:

116500.00 - 186400.00 USD / Year

Teradyne

Expiration Date

Until further notice

Requirements

2+ years of experience in machine learning, applied AI, or related fields
Hands-on experience building and deploying ML models
Exposure to production ML systems (MLOps, monitoring, deployment) is desirable
Ability to work collaboratively across teams
Strong analytical and problem-solving skills
Basic understanding of software engineering practices and version control
Ability to work cross-functionally with product, software, and hardware teams
Strong communication skills
comfortable engaging directly with customers and stakeholders
Strong problem-solving and reasoning skills

Job Responsibility

Design and implement pipelines for training, evaluation, and deployment of ML models
Apply graph ML methods to model relationships in structured and unstructured data
Build and experiment with reinforcement learning algorithms (e.g., policy gradients, PPO, Q-learning) for optimization and decision-making tasks
Incorporate interpretability and explainability techniques (e.g., SHAP, LIME, attention-based methods) into ML systems
Collaborate with software, product, and application engineering teams to integrate ML solutions into production systems
Assist in defining evaluation metrics and validation strategies for ML models
Work with internal stakeholders to understand engineering workflows and translate them into ML-driven solutions
Contribute to improving ML infrastructure, tooling, and best practices

What we offer

Medical, dental, vision, Flexible Spending Accounts, retirement savings plans, life and disability insurance, paid vacation & holidays, tuition assistance programs, and more

Fulltime

Senior Manager, Machine Learning Engineering

As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile tea...

Location

United States , McLean; New York

Salary:

229900.00 - 286200.00 USD / Year

Capital One

Expiration Date

Until further notice

Requirements

Bachelor’s Degree
At least 8 years of experience designing and building data-intensive solutions using distributed computing
At least 4 years of experience programming with Python, Scala, or Java
At least 3 years of experience building, scaling, and optimizing ML systems
At least 2 years of experience leading teams developing ML solutions
At least 4 years of people management experience
Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field
4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
3+ years of experience developing performant, resilient, and maintainable code
3+ years of experience with data gathering and preparation for ML models

Job Responsibility

Design, build, and/or deliver ML models and components that solve real-world business problems
Inform ML infrastructure decisions using understanding of ML modeling techniques and issues
Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
Collaborate as part of a cross-functional Agile team to create and enhance software
Retrain, maintain, and monitor models in production
Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale
Construct optimized data pipelines to feed ML models
Leverage continuous integration and continuous deployment best practices
Ensure all code is well-managed to reduce vulnerabilities, models are well-governed
Use programming languages like Python, Scala, or Java

What we offer

Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
comprehensive, competitive, and inclusive set of health, financial and other benefits

Fulltime

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Software Engineering, Machine Learning

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