Software-Engineer, Machine-Learning-Engineer, AI-Engineer Jobs

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.

Netflix is the world's leading streaming entertainment service, with 278 million paid members in over 190 countries, enjoying TV series, feature films, and games across numerous genres and languages. Members can watch or play as much as they want, anytime, anywhere, on any internet-connected screen.

Machine Learning/Artificial Intelligence powers innovation in all areas of the business, from helping members choose the right title for them through personalization, to better understanding our audience and our content slate, to optimizing our payment processing and other revenue-focused initiatives. Building highly scalable and differentiated ML infrastructure is key to accelerating this innovation.

The Opportunity

We are looking for a senior engineer with deep expertise in distributed model training and the systems required to operate it at scale. You will help shape the architecture of our training platform, improve performance and reliability for large training jobs, and build intuitive platform experiences for ML engineers. Our infrastructure is built on Kubernetes, Ray clusters, and PyTorch distributed training primitives.

This role requires strong technical depth, sound engineering judgment, and the ability to influence across teams. You will partner closely with ML engineers, researchers, infrastructure teams, and platform stakeholders to identify needs, lead technical discussions, drive alignment, and deliver high-impact capabilities.

charter is to maximize the business impact of all AI use cases at Netflix through highly reliable and flexible AI tooling and infrastructure that supports key product functions such as personalized recommendations, studio algorithms, virtual productions, growth intelligence, and content demand modeling among others.

In this role you will get to:

• Design and build the platform that powers large-scale machine learning model training, fine-tuning, model transformation and evaluations workflows and use cases from the entire company

• Co-design and optimize the systems and models to scale up and increase the cost-effectiveness of machine learning model training

• Design easy-to-use APIs and interfaces for experienced ML practitioners, as well as non-experts to easy access the training platform

Minimum Job Qualifications

• Design, build, and operate platform infrastructure, libraries, and SDKs for large-scale model training. Enable reliable and efficient training workflows for foundation models and generative AI models of all sizes.

• Diagnose and optimize the performance of large distributed training jobs, including GPU utilization, memory efficiency, communication overhead, data loading, checkpointing, fault tolerance, and cluster utilization.

• Experience with cloud computing providers, preferably AWS

• Comfortable with ambiguity and working across multiple layers of the tech stack to execute on both 0-to-1 and 1-to-100 projects

• Adopt and promote best practices in operations, including observability, logging, reporting, and on-call processes to ensure engineering excellence.

• Excellent written and verbal communication skills

• Comfortable working in a team with peers and partners distributed across (US) geographies & time zones.

Preferred Qualifications

• Understand modern and real-world Machine Learning model development workflows and experience partnering closely with ML modeling engineers. Lead technical design reviews, facilitate cross-functional discussions, communicate tradeoffs clearly, and align stakeholders on platform direction and execution priorities.

• Familiarity with cloud-based AI/ML services (e.g., SageMaker, Bedrock, Databricks, OpenAI, etc.)

• Familiarity with distributed training performance analysis tools and techniques, such as PyTorch Profiler, NVIDIA Nsight Systems, GPU telemetry, communication profiling, or cluster-level utilization analysis.

• Experience with large-scale distributed training and different parallelism techniques for scaling up training, such as FSDP and tensor/pipeline parallelism

• Expertise in the area of Generative AI, specifically when it comes to training foundation models, fine-tuning them, and distilling them to smaller models

Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $466,000.00 - $750,000.00. This compensation range will vary based on location.

Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here.

Netflix is a unique culture and environment. Learn more here.

Inclusionis a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.

We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.

Job is open for no less than 7 days and will be removed when the position is filled.

Originally posted on Himalayas

Chamberlain Group (CG) is a global leader in intelligent access and Blackstone portfolio company. Powered by our myQ technology, we make access simple and secure for millions of homeowners, businesses, and communities worldwide. Our flagship brands, LiftMaster® and Chamberlain® , are found in 51+ million homes, and 14 million+ people rely on the myQ® app daily.

This role is central to our mission of enhancing everyday intelligence in connected systems. This role will be responsible for building robust pipelines that analyze temporal behavior, identify anomalies, and trigger intelligent alerts.

Job Responsibilities:

• Design, develop, and deploy machine learning models for detecting anomalies in time-series data from connected devices (e.g., cameras, door sensors, access logs).
• Build pipelines that analyze historical patterns and identify deviations using a combination of statistical, classical ML, and deep learning approaches.
• Collaborate with data engineering and platform teams to ensure real-time model inference, stream processing, and alert triggering
• Tune models for low false positives and high sensitivity while maintaining operational efficiency.
• Develop and manage ML Ops pipelines for training, testing, deployment, and monitoring of anomaly detection systems
• Implement robust monitoring and feedback loops to adapt to behavior drift or seasonal variations.
• Contribute to overall AI system architecture and collaborate with engineers working on LLM-based assistants and agentic AI to ensure seamless integration.
• Work across product, engineering, and AI research teams to ensure scalable and performant deployment of models
• Drive decision-making around tooling, infrastructure, observability, and production-readiness.
• Mentor engineers across the org in AI-native engineering patterns, architecture, and LLM ecosystem evolution
• Manage, mentor, and grow a team of applied AI and full-stack engineers.
• Guide career development. Hire top talent and build a strong, collaborative team culture.
• Comply with health and safety guidelines and rules; managers should also ensure compliance across their teams.
• Protect Chamberlain Group’s reputation by keeping information confidential.
• Maintain professional and technical knowledge by attending educational workshops, reading professional publications, establishing personal networks, and participating in professional societies.
• Contribute to the team effort by accomplishing related results and participating on projects as needed.

Job Requirements:

• Bachelor’s or Master’s degree in Computer Science
• 10+ years of experience software engineering experience with 5+ in ML engineering or data science with a focus on real-time systems, behavior modeling, or time-series data.
• Proven experience building and deploying anomaly detection systems in production.
• Hands-on experience with time-series libraries (e.g., Prophet, Darts, GluonTS, Kats, Merlion).
• Experience working with event-driven architectures, edge devices, or smart home / IoT environments is a plus.
• Familiarity with vector databases or integration with LLMs

Knowledge, Skills, and Abilities:

• Strong understanding of time-series analysis, including: Trend/seasonality decomposition, Statistical anomaly detection methods (ARIMA, z-score, moving average), Classical ML techniques (Isolation Forest, One-Class SVM, clustering-based approaches), Deep learning for sequences (LSTM, GRU, TCN, Transformers)
• Experience in streaming data processing and building pipelines that operate on live or near-real-time data.
• Knowledge of change point detection, event modeling, and alert systems.
• Ability to design interpretable anomaly detection systems with threshold tuning, confidence scoring, and alert escalation.
• Understanding of MLOps principles, including CI/CD for ML, versioning, and retraining strategies.
• Strong programming skills in Python and familiarity with ML frameworks (scikit-learn, PyTorch, TensorFlow).
• Proficient in data handling and engineering tools such as Pandas, NumPy, Kafka, Spark, or Flink

Other:

• Ability to travel up to 10% of the time domestically and internationally

Preferred Job Requirements:

• Master’s degree in Computer Science, Computer Engineering, or related field
• Experience in IoT, software services, video, and AI
• Analytical and systems thinker who can reason about behavioral patterns over time
• Detail-oriented with a strong focus on data integrity and alert quality
• Comfortable operating in a fast-paced environment and building 0-1 systems
• Effective communicator — able to explain models, metrics, and uncertainty clearly to technical and non-technical stakeholders
• Experience with consumer electronics, smart home companies will be beneficial

The pay range for this position is $148,912.00 - $254,054.00; base pay offered may vary depending on a number of factors including, but not limited to, the position offered, location, education, training, and/or experience. In addition to base pay, also offered is a comprehensive benefits package and 401k contribution (all benefits are subject to eligibility requirements). This position is eligible for participation in a short-term incentive plan subject to the terms of the applicable plans and policies.

Chamberlain Group wants all of its employees to succeed and encourages people of all backgrounds to apply. We’re proud to be an Equal Opportunity Employer, and you’ll be considered for this role regardless of race, color, religion, sex, national origin, age, sexual orientation, ancestry; marital, disabled or veteran status. We’re committed to fostering an environment where people of all lived experiences feel welcome.

Persons with disabilities who anticipate needing accommodations for any part of the application process may contact, in confidence .

NOTE: Staffing agencies, headhunters, recruiters, and/or placement agencies, please do not contact our hiring managers directly.

Originally posted on Himalayas