Machine Learning Engineer
Design, train, and fine-tune high-performance machine learning models for security detection use cases. Build scalable ML infrastructure and optimize production inference pipelines for latency, cost, and reliability.
Remote Machine Learning Engineer Jobs in India (23)
Machine Learning Engineer
Design, train, and productionize deep learning models for speech, audio, and computer vision domains. Own the end-to-end lifecycle from dataset curation and architecture design to deployment and performance monitoring.
Machine Learning Engineer
Collaborate with Data Science teams to implement and integrate ML algorithms into production code. Focus on ensuring performance, scalability, and the application of coding best practices within Scrum teams.
Machine Learning Engineer - III
You will lead a team in designing and implementing a large language model framework to power diverse applications across the company. Your role covers the entire development lifecycle, from conceptualization and prototyping to the delivery of platform features.
Machine Learning Engineer IV
Design, build, and improve production-grade machine learning systems for classification, document understanding, and AI-powered automation. Contribute to GenAI platform capabilities while ensuring high reliability, observability, and security across all model-serving workflows.
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Senior Machine Learning Engineer
You will own the end-to-end machine learning lifecycle, from research and model development to deployment and scaling in production environments. You will work directly with product teams to design algorithms for visibility, demand forecasting, and freight audit while ensuring system reliability and performance.
Principal Machine Learning Engineer
You will set the technical direction for AI initiatives within Jira Service Management, designing and optimizing multi-step LLM pipelines. Additionally, you will own the quality, reliability, and performance of AI workflows while mentoring emerging engineers and driving long-term ML strategy.
Principal Machine Learning Engineer
The Principal Machine Learning Engineer will build and optimize machine learning models while designing and maintaining the necessary infrastructure. They will collaborate with cross-functional teams to establish data pipelines and deliver production-grade ML services for the company platform.
Machine Learning Engineer - IV (Computer Vision)
Lead the design and scaling of production-grade computer vision systems for biometrics, including face recognition and attribute detection. Own the end-to-end ML pipeline from data ingestion and curation to low-latency deployment on AWS.
Machine Learning Engineer - IV (Fraud)
Develop and maintain advanced machine learning and computer vision models to detect fraud for identity verification. Deploy these models via AWS SageMaker or on-device and collaborate with product managers in an Agile environment.
Machine Learning Engineer, Reliability
Own the reliability, security, and safety of generative media model APIs to ensure high availability and performance. Build monitoring systems to detect ML-specific failures and lead incident response for model API outages.
Staff Machine Learning Engineer (Employer of Record)
Lead the design, development, and scaling of AI-powered solutions and enterprise-grade LLM systems to solve complex business challenges. Partner with stakeholders to define strategic roadmaps and mentor other machine learning engineers on design and coding standards.
Senior Machine Learning Engineer
Design, develop, and deploy scalable LLM-powered systems and agentic pipelines to enhance real estate operations and customer experience. Collaborate across departments to integrate AI solutions into product development and maintain production-grade AI architectures.
Machine Learning Engineer with an Agentic Focus
The role involves designing, developing, and deploying machine learning models and solutions, utilizing tools like LangGraph and MLflow for orchestration and lifecycle management. Responsibilities also include building scalable data pipelines using GCP services and implementing robust monitoring strategies for model performance and reliability.
![Smart Working Solutions is hiring for remote Machine Learning Engineer (Mid/Senior) (Remote, Full-Time) [AS221]](/assets/08150176-369d-44db-a4a7-778571334971.png){kind=small}
Machine Learning Engineer (Mid/Senior) (Remote, Full-Time) [AS221]
The Machine Learning Engineer will be responsible for driving the development and integration of AI capabilities by building end-to-end ML solutions, from data modeling through to system deployment. Key tasks include automating complex processes, translating business problems into scalable ML solutions, and promoting machine learning best practices across the organization.
Senior Machine Learning Engineer, Gen AI
The role involves designing and developing machine learning infrastructure, tooling, and models to enable teams to deliver world-class experiences and build internal platforms for incorporating AI features. You will also consult with teams on machine learning patterns, tradeoffs, and guide them through creating excellent end-to-end customer experiences.
Senior Machine Learning Engineer (Library)
The role involves building and productionizing core ML components, focusing on LLM and NLP models for search, summarization, and generative tasks by developing optimized pipelines and prompt strategies. Responsibilities also include designing scalable ML services and inference pipelines in Python, ensuring robust engineering discipline through testing and observability.
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Machine Learning Engineer - IV (Biometrics)
The role involves leading the design and development of computer vision systems for biometrics, including rigorous fairness analysis and benchmarking of models. Responsibilities also include owning end-to-end ML pipelines from data ingestion to deployment and optimizing models for low-latency inference.
Machine Learning Engineer (Remote)
The Machine Learning Engineer will work closely with the Data Science team to develop and implement ML algorithms into production code. They will ensure that algorithms are optimized for performance and scalability while collaborating with cross-functional teams.
Senior Machine Learning Operations Engineer
Architect and maintain the machine learning production lifecycle by designing scalable infrastructure and automation pipelines. Collaborate cross-functionally to deploy, monitor, and optimize AI models to ensure high performance and security.
AI Engineer | Python | AI Agents | Machine Learning | Full Stack | Remote
Design and deploy intelligent AI agents and machine learning models using frameworks like LangChain and TensorFlow. Integrate these AI capabilities into full-stack web applications and manage scalable data pipelines on AWS.
AI Engineer | Python | AI Agents | Chatbots | Machine Learning | Full Stack | Remote
Develop and deploy machine learning models and build backend systems using Python. Integrate AI solutions with full-stack applications and develop REST APIs.
Senior Machine Learning Systems Engineering Manager - AI & ML Platform
Lead the AI & ML Platform team to build and run infrastructure that supports generative LLMs, model serving, and data training. Focus on coaching engineers, driving technical standards, and collaborating with stakeholders to influence the platform's strategic direction.
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