Senior Machine Learning Engineer #7405 at New Relic Inc Canada

Hyderabad, Telangana, India -

Full Time

Start Date

Immediate

Expiry Date

08 Apr, 26

Salary

0.0

Posted On

08 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Conversational AI, Python, Kubernetes, C++, Kotlin, NLP, PyTorch, Tensorflow, HuggingFace Transformers, SpaCy, Kafka, RabbitMQ, AirFlow, Sagemaker, Model Deployment

Industry

Software Development

Description

We are a global team of innovators and pioneers dedicated to shaping the future of observability. At New Relic, we build an intelligent platform that empowers companies to thrive in an AI-first world by giving them unparalleled insight into their complex systems. As we continue to expand our global footprint, we're looking for passionate people to join our mission. If you're ready to help the world's best companies optimize their digital applications, we invite you to explore a career with us! Your opportunity As a crucial member of our team, you'll play a pivotal role across the entire machine learning lifecycle, contributing to our conversational AI bots, RAG system and traditional ML problem solving for our observability platform. Your tasks will encompass both operational and engineering aspects, including building production-ready inference pipelines, deploying and versioning models, and implementing continuous validation processes. On the LLM side you'll fine-tune generative AI models, design agentic language chains, and prototype recommender system experiments. What you'll do In this role, you'll have the opportunity to contribute significantly to our machine learning initiatives, shaping the future of AI-driven solutions in various domains. If you're passionate about pushing the boundaries of what's possible in machine learning and ready to take on diverse challenges, we encourage you to apply and join us in our journey towards innovation. This role requires Proficiency in software engineering design practices. Experience working with transformer models and text embeddings. Proven track record of deploying and managing ML models in production environments. Familiarity with common ML/NLP libraries such as PyTorch, Tensorflow, HuggingFace Transformers, and SpaCy. 5+ years of developing production-grade applications in Python. Proficiency in Kubernetes and containers. Familiarity with concepts/libraries such as sklearn, kubeflow, argo, and seldon. Expertise in Python, C++, Kotlin, or similar programming languages. Experience designing, developing, and testing scalable distributed systems. Familiarity with message broker systems (e.g., Kafka, RabbitMQ). Knowledge of application instrumentation and monitoring practices. Experience with ML workflow management, like AirFlow, Sagemaker, etc. Fine-tuning generative AI models to enhance performance. Designing AI Agents for conversational AI applications. Experimenting with new techniques to develop models for observability use cases Building and maintaining inference pipelines for efficient model deployment. Managing deployment and model versioning pipelines for seamless updates. Developing tooling to continuously validate models in production environments. Bonus points if you have Familiarity with the AWS ecosystem. Past projects involving the construction of agentic language chains Please note that visa sponsorship is not available for this position. Fostering a diverse, welcoming and inclusive environment is important to us. We work hard to make everyone feel comfortable bringing their best, most authentic selves to work every day. We celebrate our talented Relics’ different backgrounds and abilities, and recognize the different paths they took to reach us – including nontraditional ones. Their experiences and perspectives inspire us to make our products and company the best they can be. We’re looking for people who feel connected to our mission and values, not just candidates who check off all the boxes. If you require a reasonable accommodation to complete any part of the application or recruiting process, please reach out to resume@newrelic.com. We believe in empowering all Relics to achieve professional and business success through a flexible workforce model. This model allows us to work in a variety of workplaces that best support our success, including fully office-based, fully remote, or hybrid. Our hiring process In compliance with applicable law, all persons hired will be required to verify identity and eligibility to work and to complete employment eligibility verification. Note: Our stewardship of the data of thousands of customers means that a criminal background check is required to join New Relic. We will consider qualified applicants with arrest and conviction records based on individual circumstances and in accordance with applicable law including, but not limited to, the San Francisco Fair Chance Ordinance. Headhunters and recruitment agencies may not submit resumes/CVs through this website or directly to managers. New Relic does not accept unsolicited headhunter and agency resumes, and will not pay fees to any third-party agency or company that does not have a signed agreement with New Relic. New Relic develops and distributes encryption software and technology that complies with U.S. export controls and licensing requirements. Certain New Relic roles require candidates to pass an export compliance assessment as a condition of employment in any global location. If relevant, we will provide more information later in the application process. Candidates are evaluated based on qualifications, regardless of race, religion, ethnicity, national origin, sex, sexual orientation, gender expression or identity, age, disability, neurodiversity, veteran or marital status, political viewpoint, or other legally protected characteristics. Review our Applicant Privacy Notice at https://newrelic.com/termsandconditions/applicant-privacy-policy

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Responsibilities

You will play a pivotal role across the entire machine learning lifecycle, contributing to conversational AI bots and traditional ML problem solving. Your tasks will include building production-ready inference pipelines and deploying models.