3 Drift Detection Jobs

You should have at least 5+ years of experience for this role. As a key member of the team, your responsibilities will include scoping, developing, expanding, operating, and maintaining scalable, reliable, and safe generative AI solutions. Your expertise will be crucial in designing and executing engineering experiments to optimize Large Language Models (LLMs) for various use cases. Collaborating with Subject Matter Experts (SMEs) to evaluate prompt effectiveness and align AI solutions with business needs will be an essential part of your role. You will need to understand and apply offline and online evaluation metrics for LLMs to ensure continuous model improvements. Additionally, you will be responsible for evaluating production models using live data, implementing robust monitoring systems in the absence of ground metrics, and monitoring LLM applications for model drift, hallucinations, and performance degradation. Your role will also involve ensuring the smooth integration of LLMs into existing workflows, providing real-time insights, and predictive analytics. For Data Scientists, we are looking for individuals with proven experience in data science, expertise in managing structured and unstructured data, proficiency in statistical techniques, predictive analytics, and reporting results. Experience in applied science in fields like Natural Language Processing (NLP), Machine Learning (ML), Deep Learning (DL), or Multimodal Analysis is preferred. A strong background in software development, data modeling, or data engineering is necessary, along with a deep understanding of building and scaling ML models, specifically LLMs. Familiarity with open-source tools such as PyTorch, statistical analysis, and data visualization tools is a plus, as well as experience with vector databases and graph databases. For AI/ML Engineers, we are seeking candidates with solid experience in business analytics, data science, software development, and data engineering. Expertise in Python and frameworks such as PyTorch, TensorFlow, or ONNX is required. Hands-on experience working with LLMs and Generative AI, including model development and inference patterns, is essential. You should have a proven ability to design scalable systems leveraging LLMs, particularly in distributed computing environments. Preferred skills for this role include experience in prompt engineering and prompt optimization, expertise in running experiments to evaluate generative AI performance, knowledge of production-level monitoring tools for ML models, including drift detection and mitigation strategies, excellent problem-solving skills, and the ability to work cross-functionally with data scientists, engineers, and SMEs. Experience with safety, security, and responsible use of AI, red-teaming (adversarial testing) of generative AI, and developing AI applications with sensitive data such as PHI, PII, and highly confidential data will be an advantage.,

As a Data Scientist and LLM Operations Specialist, you will need to have a minimum of 5+ years of experience in the field. Your primary responsibilities will include managing both structured and unstructured data with expertise in statistical techniques, predictive analytics, and reporting results. Additionally, you will be required to apply your skills in Natural Language Processing (NLP), Machine Learning (ML), Deep Learning (DL), and Multimodal Analysis. Your background should demonstrate a strong foundation in software development, data modeling, and data engineering. You must possess a deep understanding of building and scaling ML models, specifically LLMs, and be familiar with open-source tools like PyTorch, statistical analysis, and data visualization tools. Experience with vector databases and graph databases would be advantageous for this role. For the AI/ML Engineer position, you should have solid experience in business analytics, data science, software development, and data engineering. Proficiency in Python and frameworks such as PyTorch, TensorFlow, or ONNX is essential. Hands-on experience with LLMs and Generative AI, including model development and inference patterns, is crucial. You should also be capable of designing scalable systems using LLMs in distributed computing environments. Preferred skills for this role include expertise in prompt engineering, prompt optimization, and running experiments to evaluate generative AI performance. Knowledge of production-level monitoring tools for ML models, along with excellent problem-solving skills, is highly valued. You should be comfortable working cross-functionally with data scientists, engineers, and subject matter experts. Experience with safety, security, and responsible use of AI, as well as red-teaming of generative AI, would be beneficial. Previous experience in developing AI applications with sensitive data such as PHI, PII, and highly confidential data is also desirable. This position is contractual/temporary for a duration of 6 months, with the possibility of extension. The work schedule is during the day shift, and the job location is in Bangalore. If selected, you will be expected to join immediately or within a notice period of 15 days. Please be prepared to discuss your overall experience, comfort with a 6-month contract position, years of experience in Data Science & Machine Learning, expertise in NLP, Deep Learning, and Multimodal Analysis, as well as your experience with ML models, LLMs, managing structured and unstructured data, statistical techniques, predictive analytics, and various tools such as PyTorch, TensorFlow, and ONNX. Additionally, you will be asked about your experience in Data Modeling, Data Engineering, and your current and expected CTC. Should you meet the requirements and be selected for this role, you will be expected to work in person at the specified location.,

You are a highly experienced Senior Python & AI Engineer who will lead the development of innovative AI/ML solutions. Your strong background in Python programming, deep learning, machine learning, and proven leadership skills will drive the team towards delivering high-quality AI systems. You will architect solutions, define technical strategies, mentor team members, and ensure timely project deliveries. In the technical realm, you will be responsible for designing and implementing scalable AI/ML systems and backend services using Python. Your role includes overseeing the development of machine learning pipelines, APIs, and model deployment workflows. Reviewing code, establishing best practices, and maintaining technical quality across the team will be key aspects of your responsibilities. As a team leader, you will guide data scientists, ML engineers, and Python developers, providing mentorship, coaching, and conducting performance evaluations. You will facilitate agile practices such as sprint planning, daily stand-ups, and retrospectives. Collaboration with cross-functional teams, including product, QA, DevOps, and UI/UX, will be essential for timely feature deliveries. In AI/ML development, you will develop and optimize models for NLP, computer vision, or structured data analysis based on project requirements. Implementing model monitoring, drift detection, and retraining strategies will contribute to the success of AI initiatives. You will work closely with product managers to translate business needs into technical solutions and ensure the end-to-end delivery of features meeting performance and reliability standards. Your technical skills should include over 5 years of Python experience, 2+ years in AI/ML projects, a deep understanding of ML/DL concepts, and proficiency in frameworks like PyTorch, TensorFlow, and scikit-learn. Experience with deployment tools, cloud platforms, and CI/CD pipelines is required. Leadership qualities such as planning, estimation, and effective communication are also crucial, with at least 3 years of experience leading engineering or AI teams. Preferred qualifications include a Masters or PhD in relevant fields, exposure to MLOps practices, and familiarity with advanced AI technologies. Prior experience in fast-paced startup environments is a plus. In return, you will have the opportunity to spearhead cutting-edge AI initiatives, face diverse challenges, enjoy autonomy, and receive competitive compensation with performance-based incentives.,