14 Nlp Algorithms Jobs

As a Senior Data Scientist, you will play a crucial role in supporting the design, development, and implementation of generative AI models and systems. Your responsibilities will include assisting in model development, algorithm optimization, data preprocessing, feature engineering, model evaluation, and collaboration with cross-functional teams. You will focus on learning and developing your skills in generative AI while ensuring ethical considerations are adhered to under the guidance of senior team members. Your technical skills should include in-depth knowledge of ML, Deep Learning, NLP algorithms, and experience with ML platforms like GCP Vertex AI, Azure AI Foundry, or AWS SageMaker. Proficiency in Python, Java, or C++, along with machine learning frameworks such as TensorFlow or PyTorch, is essential for developing and optimizing generative AI models. Cloud computing experience, particularly with Google or Azure Cloud Platform, is crucial, as well as an understanding of Data Analytics Services offered by these platforms. Preferred technical skills may include knowledge of Azure Cognitive Search, Google Cloud Search, AWS Kendra, and experience in large-scale deployment of ML projects with a good understanding of DevOps/MLOps/LLM Ops. Strong communication skills, the ability to work independently, mentor junior developers, and understand business objectives to support data needs are key behavioral attributes required for this role. To qualify for this position, you should hold a Bachelors or Masters degree in Computer Science and possess 6 to 8 years of relevant work experience. If you are looking to contribute to cutting-edge generative AI projects, collaborate with diverse teams, and stay updated with the latest AI trends, this role is ideal for you.,

As a Senior Generative AI Engineer, your primary role will involve conducting original research on generative AI models. You will focus on exploring model architecture, training methodologies, fine-tuning techniques, and evaluation strategies. It is essential to maintain a strong publication record in esteemed conferences and journals, demonstrating your valuable contributions to the fields of Natural Language Processing (NLP), Deep Learning (DL), and Machine Learning (ML). In addition, you will be responsible for designing and experimenting with multimodal generative models that incorporate various data types such as text, images, and other modalities to enhance AI capabilities. Your expertise will be crucial in developing autonomous AI systems that exhibit agentic behavior, enabling them to make independent decisions and adapt to dynamic environments. Leading the design, development, and implementation of generative AI models and systems will be a key aspect of your role. This involves selecting suitable models, training them on extensive datasets, fine-tuning hyperparameters, and optimizing overall performance. It is imperative to have a deep understanding of the problem domain to ensure effective model development and implementation. Furthermore, you will be tasked with optimizing generative AI algorithms to enhance their efficiency, scalability, and computational performance. Techniques such as parallelization, distributed computing, and hardware acceleration will be utilized to maximize the capabilities of modern computing architectures. Managing large datasets through data preprocessing and feature engineering to extract critical information for generative AI models will also be a crucial aspect of your responsibilities. Your role will also involve evaluating the performance of generative AI models using relevant metrics and validation techniques. By conducting experiments, analyzing results, and iteratively refining models, you will work towards achieving desired performance benchmarks. Providing technical leadership and mentorship to junior team members, guiding their development in generative AI, will also be part of your responsibilities. Documenting research findings, model architectures, methodologies, and experimental results thoroughly is essential. You will prepare technical reports, presentations, and whitepapers to effectively communicate insights and findings to stakeholders. Additionally, staying updated on the latest advancements in generative AI by reading research papers, attending conferences, and engaging with relevant communities is crucial to foster a culture of learning and innovation within the team. Mandatory technical skills for this role include strong programming abilities in Python and familiarity with frameworks like PyTorch or TensorFlow. In-depth knowledge of Deep Learning concepts such as CNN, RNN, LSTM, Transformers LLMs (BERT, GEPT, etc.), and NLP algorithms is required. Experience with frameworks like Langgraph, CrewAI, or Autogen for developing, deploying, and evaluating AI agents is also essential. Preferred technical skills include expertise in cloud computing, particularly with Google/AWS/Azure Cloud Platform, and understanding Data Analytics Services offered by these platforms. Hands-on experience with ML platforms like GCP: Vertex AI, Azure: AI Foundry, or AWS SageMaker is desirable. Strong communication skills, the ability to work independently with minimal supervision, and a proactive approach to escalate when necessary are also key attributes for this role. If you have a Master's or PhD degree in Computer Science and 6 to 8 years of experience with a strong record of publications in top-tier conferences and journals, this role could be a great fit for you. Preference will be given to research scholars from esteemed institutions like IITs, NITs, and IIITs.,

Apple is a place where individual imaginations gather together, committing to the values that lead to great work. Every new product built or service created is the result of making each other's ideas stronger. This collaborative environment is fueled by the shared belief that something wonderful can be created and shared with the world, ultimately changing lives for the better. The diversity of the team members and their thinking inspires innovation that permeates through everything that is done at Apple. By bringing everybody in, the best work of their lives can be achieved. When you join Apple, you are not just joining something, you are adding something. Product Engineering International, part of the esteemed Software Engineering Organization, is seeking an accomplished ML Researcher to spearhead the development of cutting-edge generative modeling pipelines for a diverse range of popular international languages. In this pivotal role, you will be at the forefront of natural language processing, designing and implementing end-to-end solutions. Your responsibilities will include driving innovation in generative modeling, owning the entire generative modeling pipeline, and prioritizing working with a variety of popular international languages to ensure culturally and linguistically adaptable models. As a key pillar of Apple Intelligence, you will bring impact to billions of users with your ML expertise, engineering passion, and programming skills. You will collaborate with a dedicated team of outstanding ML and software engineers on advanced text generation technologies. The focus will be on generative technologies for key international markets to ensure top-class experiences for the popular languages in these markets. Minimum Qualifications: - 4+ years of machine learning expertise. - Strong programming skills using Python/Objective C/Swift. - Good exposure to Deep Learning libraries like PyTorch and TensorFlow. - Thorough experience with common NLP algorithms and applications, including tokenization, language modeling, text decoding, text classifier, etc. Preferred Qualifications: - Actively exercising machine learning techniques, including implementing basic optimizers and regularizations. - Actively programming with high-quality codes across complex and large repositories. - Experience of multi-modal modeling. - Experience in NLP modeling for Indian languages is desired. If you are a passionate ML researcher with a deep interest in natural language processing and a talent for building generative models that work seamlessly across languages, join our team and make a meaningful impact!,

Are you ready to be a part of something big Join our team at SoundHound AI, where AI innovation and real-world impact come together. We unite voice AI, generative AI, and conversational AI to deliver powerful AI solutions that reimagine how people interact with the products and services they rely on. Whether it's voice-enabling vehicles, streamlining patient journeys, or enhancing customer service, our multilingual, omnichannel AI technology touches the lives of hundreds of millions of people around the world. We are looking for a Software Engineer with native-level proficiency in speaking Tamil and an interest in creating user-friendly VoiceAI products using C++. You will learn and apply the most advanced technologies in the fields of Natural Language Processing (NLP), Natural Language Understanding (NLU), Natural Language Generation (NLG), speech, and search, all built in-house at SoundHound. Prior experience in these specialized fields is not required. We are a highly collaborative, internationally dispersed team. We've worked hard to build a platform enabling individual developers to implement deep natural language user experiences rapidly, often within days. In this role, you will simultaneously leverage your coding skills and your knowledge of the Tamil language. You will develop Conversational AI leveraging a powerful domain-oriented development paradigm and implement and scale the core codebase, solving both algorithmic and design challenges. You will write code that interacts with third-party APIs and collaborate closely with engineers who are building similar features for a variety of languages. We would love to hear from you if you have a Bachelor's Degree in Computer Science and at least 2 years of experience as a Software Engineer OR a Masters Degree in Computer Science. You should have excellent coding skills in C++ and at least one scripting language, design unit and integration tests, and maintain rigorous standards for code quality. Being fluent in Tamil and English, passionate about working at the intersection of software engineering and linguistics, and experienced in designing efficient architectures, algorithms, and interfaces are desired qualifications. Additionally, enjoying working on complex, open-ended challenges and improving existing solutions, as well as being comfortable in a Linux environment, are important attributes. We'd be especially excited if you have built chatbots or voice assistants or have experience with NLP algorithms. By working at SoundHound AI, you will join hundreds of employees across the globe who strive every day to create exceptional AI-powered experiences for customers, employees, and patients. We are a values-driven company that is supportive of one another, open and honest, undaunted by challenges, nimble and focused, and determined to excel and win. Our mission is to build voice AI for the world and use our global, diverse perspectives to achieve real generational breakthroughs. SoundHound ensures that individuals with disabilities are provided reasonable accommodations to participate in the interview process, perform essential job functions, and receive other employment benefits. Learn more about our philosophy, benefits, and culture at [SoundHound Careers](https://www.soundhound.com/careers). To view our job applicant privacy policy, please visit [Applicant Privacy Notice](https://static.soundhound.com/corpus/ta/applicantprivacynotice.html).,

Strong Python and intermediate SQL skills Experience building, deploying, and evaluating ML/NLP/GenAI systems. Experience with ML system design Very strong (including written) communication skills and ability to break down and articulate complex tasks into implementation strategies Software engineering best practices, including testing, OOP, etc. Knowledge of cloud systems, especially azure preferred. A more traditional ML perspective, some knowledge and understanding of mathematical optimizers, how to select the best ones for purpose and set parameters Must Have: Experience working closely with other data scientists, data engineers software engineers, data managers and business partners. Can build scalable, re-usable, impactful data science products, usually containing statistical or machine learning algorithms, in collaboration with data engineers and software engineers. Can carry out data analyses to yield actionable business insights. Hands-on experience (typically 5+ years) designing, planning, prototyping, productionizing, maintaining and documenting reliable and scalable data science products in complex environments. Applied knowledge of data science tools and approaches across all data lifecycle stages. Thorough understanding of underlying mathematical foundations of statistics and machine learning. Development experience in one or more object-oriented programming languages (e.g. Python, Go, Java, C++) Advanced SQL knowledge. Knowledge of experimental design and analysis. Customer-centric and pragmatic mindset. Focus on value delivery and swift execution, while maintaining attention to detail. Strong software engineering and ML system design experience. Experience with system designs like kNN model, NLP algorithms.

Strong Python and intermediate SQL skills Experience building, deploying, and evaluating ML/NLP/GenAI systems. Experience with ML system design Very strong (including written) communication skills and ability to break down and articulate complex tasks into implementation strategies Software engineering best practices, including testing, OOP, etc. Knowledge of cloud systems, especially azure preferred. A more traditional ML perspective, some knowledge and understanding of mathematical optimizers, how to select the best ones for purpose and set parameters Must Have: Experience working closely with other data scientists, data engineers software engineers, data managers and business partners. Can build scalable, re-usable, impactful data science products, usually containing statistical or machine learning algorithms, in collaboration with data engineers and software engineers. Can carry out data analyses to yield actionable business insights. Hands-on experience (typically 5+ years) designing, planning, prototyping, productionizing, maintaining and documenting reliable and scalable data science products in complex environments. Applied knowledge of data science tools and approaches across all data lifecycle stages. Thorough understanding of underlying mathematical foundations of statistics and machine learning. Development experience in one or more object-oriented programming languages (e.g. Python, Go, Java, C++) Advanced SQL knowledge. Knowledge of experimental design and analysis. Customer-centric and pragmatic mindset. Focus on value delivery and swift execution, while maintaining attention to detail. Strong software engineering and ML system design experience. Experience with system designs like kNN model, NLP algorithms.

Strong Python and intermediate SQL skills Experience building, deploying, and evaluating ML/NLP/GenAI systems. Experience with ML system design Very strong (including written) communication skills and ability to break down and articulate complex tasks into implementation strategies Software engineering best practices, including testing, OOP, etc. Knowledge of cloud systems, especially azure preferred. A more traditional ML perspective, some knowledge and understanding of mathematical optimizers, how to select the best ones for purpose and set parameters Must Have: Experience working closely with other data scientists, data engineers software engineers, data managers and business partners. Can build scalable, re-usable, impactful data science products, usually containing statistical or machine learning algorithms, in collaboration with data engineers and software engineers. Can carry out data analyses to yield actionable business insights. Hands-on experience (typically 5+ years) designing, planning, prototyping, productionizing, maintaining and documenting reliable and scalable data science products in complex environments. Applied knowledge of data science tools and approaches across all data lifecycle stages. Thorough understanding of underlying mathematical foundations of statistics and machine learning. Development experience in one or more object-oriented programming languages (e.g. Python, Go, Java, C++) Advanced SQL knowledge. Knowledge of experimental design and analysis. Customer-centric and pragmatic mindset. Focus on value delivery and swift execution, while maintaining attention to detail. Strong software engineering and ML system design experience. Experience with system designs like kNN model, NLP algorithms.

Develop and enhance AI-driven chatbot solutions to automate customer interactions and optimize response accuracy. Design and implement NLP algorithms using frameworks like Rasa, Dialogflow, or IBM Watson. Ensure seamless chatbot integration with existing platforms and CRM systems. Work closely with data scientists to improve machine learning models. Must have strong proficiency in Python, deep learning techniques, and chatbot analytics.

Develop and enhance AI-driven chatbot solutions to automate customer interactions and optimize response accuracy. Design and implement NLP algorithms using frameworks like Rasa, Dialogflow, or IBM Watson. Ensure seamless chatbot integration with existing platforms and CRM systems. Work closely with data scientists to improve machine learning models. Must have strong proficiency in Python, deep learning techniques, and chatbot analytics.

Develop and enhance AI-driven chatbot solutions to automate customer interactions and optimize response accuracy. Design and implement NLP algorithms using frameworks like Rasa, Dialogflow, or IBM Watson. Ensure seamless chatbot integration with existing platforms and CRM systems. Work closely with data scientists to improve machine learning models. Must have strong proficiency in Python, deep learning techniques, and chatbot analytics.

Develop and enhance AI-driven chatbot solutions to automate customer interactions and optimize response accuracy. Design and implement NLP algorithms using frameworks like Rasa, Dialogflow, or IBM Watson. Ensure seamless chatbot integration with existing platforms and CRM systems. Work closely with data scientists to improve machine learning models. Must have strong proficiency in Python, deep learning techniques, and chatbot analytics.

Develop and enhance AI-driven chatbot solutions to automate customer interactions and optimize response accuracy. Design and implement NLP algorithms using frameworks like Rasa, Dialogflow, or IBM Watson. Ensure seamless chatbot integration with existing platforms and CRM systems. Work closely with data scientists to improve machine learning models. Must have strong proficiency in Python, deep learning techniques, and chatbot analytics.

Develop and enhance AI-driven chatbot solutions to automate customer interactions and optimize response accuracy. Design and implement NLP algorithms using frameworks like Rasa, Dialogflow, or IBM Watson. Ensure seamless chatbot integration with existing platforms and CRM systems. Work closely with data scientists to improve machine learning models. Must have strong proficiency in Python, deep learning techniques, and chatbot analytics.

Develop and enhance AI-driven chatbot solutions to automate customer interactions and optimize response accuracy Design and implement NLP algorithms using frameworks like Rasa, Dialogflow, or IBM Watson Ensure seamless chatbot integration with existing platforms and CRM systems Work closely with data scientists to improve machine learning models Must have strong proficiency in Python, deep learning techniques, and chatbot analytics