6 Langsmith Jobs

About the Role As a Data Science Engineer, you will need strong technical skills in data modeling, machine learning, data engineering, and software development. You will have the ability to conduct literature reviews and critically evaluate research papers to identify applicable techniques. Additionally, you should be able to design and implement efficient and scalable data processing pipelines, perform exploratory data analysis, and collaborate with other teams to integrate data science models into production systems. Passion for conversational AI and a desire to solve some of the most complex problems in the Natural Language Processing space are essential. You will work on highly scalable, stable, and automated deployments, aiming for high performance. Taking on the challenge of building and scaling a truly remarkable AI platform to impact the lives of millions of customers will be part of your responsibilities. Working in a challenging yet enjoyable environment, where learning new things is the norm, you should think of solutions beyond boundaries. You should also drive outcomes with full ownership, deeply believe in customer obsession, and thrive in a fast-paced environment of learning and innovation. You will work in a challenging, consumer-facing problem space, where you can make an immediate impact. You will get to work with the latest technologies, learn to use new tools and get the opportunity to have your say in the final product. Youll work alongside a great team in an open, collaborative environment. We are part of Vimo, a well-funded, stable mid-size company with excellent salaries, medical/dental/vision coverage, and perks. Vimo is an Equal Opportunity Employer. Data Science Engineer Responsibilities: Build and maintain robust data pipelines to process data from varied sources like databases, APIs, and file systems. Harness data science tools and techniques to develop proof of concepts, evolving solutions through adept prompt engineering and fine-tuning of models like GPT. Conduct comprehensive literature reviews and critically evaluate research papers to identify innovative techniques, focusing on the latest advancements in LLM/Generative AI. Create and manage JSON APIs to expose data, machine learning services, and AI models to other systems and applications. Ensure data accuracy, completeness, and reliability through stringent quality control measures and data validation techniques. Optimize existing language models for generative AI tasks, focusing on enhancing their application across various platforms. Work in tandem with product teams to seamlessly integrate cutting-edge AI technologies, upholding the highest quality standards in product execution. Fine-tune and deploy LLMs, ensuring they are meticulously adjusted and ready for release. Engage in ongoing research and application of new methodologies to bolster the efficiency and output quality of our LLM operations. Design and develop LLMs dedicated to a range of content generation tasks, pushing the boundaries of AI's creative capabilities. Keep up to date of the latest trends and breakthroughs in NLP and large language model technology, incorporating novel approaches to refine our models. Lead experiments and analyses to fine-tune model designs and hyperparameters, ensuring superior model performance with continuous monitoring using KPIs and metrics. Demonstrate strong analytical and troubleshooting skills; and someone who enjoys owning and solving problems end-to-end. Excellent communication skills. Comfortable interacting with remote teams in multiple offices that practice agile methodologies. Requirements & Qualifications: Bachelors or masters degree in computer science, Engineering, Mathematics, Statistics, or a related field. Minimum of 2 years of experience in NLP oriented data engineering or data science roles with a significant emphasis on working with LLM/Generative AI models. Robust understanding of NLP concepts, with hands-on experience in conversational AI and expertise in natural language understanding and generation. Proficiency in Python programming and familiarity with libraries and frameworks such as Pandas, NumPy, Scikit-learn, Tensor flow, transformers, PyTorch, and Keras. Solid experience in building, maintaining, and fine-tuning large language models, with a keen understanding of prompt engineering techniques. Strong grasp of data architecture, database design, data modeling principles, and the integration of AI models into scalable systems. Experience with JSON APIs and building RESTful & GRPC web services. Excellent analytical and problem-solving skills, capable of working independently and collaboratively in a team-oriented environment. Showcase proven expertise in working with deep learning frameworks and LLMs, with a strong foundation in prompt engineering, tokenization, embeddings, model optimization, and deployment strategies. Demonstrate previous involvement in creating user-centric products leveraging ML/AI technologies, with a good understanding of predictive modeling, meta-learning, and transfer learning. Excellent problem-solving and communication skills BS degree in Information Technology, Computer Science, or relevant field Additional Experience We Would Love to Have Experience with cloud technologies such as AWS is a plus. Background in design and development of Technology for Government Health and Human Services Experience with design and development of SaaS solutions.

We are seeking a highly skilled Generative AI Consulting Director to join our dynamic team, where they will lead our consulting team, manage the delivery of consulting services, guide clients through the implementation of our Gen AI platform, and ensure the successful adoption of the platform across industries. Key Responsibilities: Lead or mentor a global team of AI consultants, solution architects, and professional services teams. Develop and execute the strategy for consulting and professional services for the Gen AI platform. Manage the end-to-end Implementation our platform in client environments, ensuring high quality implementations, on time delivery, and alignment with customer expectations. Work closely with clients to understand their business challenges and design tailored solutions using the Gen AI platform. Lead the development of solution architectures, ensuring that proposed solutions are scalable, innovative, and aligned with the client's objectives. Collaborate with product development, GTM, and engineering teams to ensure successful implementation and integrations. Provide feedback to product teams based on client needs and market trends to continuously improve the platforms offerings. Drive client success by ensuring that Gen AI platform implementation deliver measurable value and return on investment (ROI). Work closely with clients to define successful metrics, track project outcomes, and guide the optimization of AI models and systems post-implementation. Manage P&L for the Consulting and Professional Services division, ensuring profitability through effective project management, cost control, and client retention. Develop and implement strategies to drive revenue growth within the professional services arm. Ethical and Responsible AI: Adhere to ethical AI practices, such as fairness, transparency, and accountability. Address biases and potential risks associated with AI systems to ensure responsible deployment and usage. Research and Innovation: Stay updated with the latest advancements in AI technologies, frameworks, and algorithms. Conduct research and experimentation to explore innovative approaches and techniques that can enhance AI capabilities. Mandatory Qualifications/Skills: A bachelors or masters degree, or equivalent, in computer science, Artificial Intelligence, or a related field. 15+ years of experience in consulting or professional services, with at least 5 years in a leadership role overseeing a team of AI consultants or solution architects Extensive experience in delivering Generative AI solutions and familiarity with AI platforms, including knowledge of NLP, deep learning, and reinforcement learning. Experience with large language models (LLMs) and prompt engineering. Solid understanding of various fine-tuning techniques like full fine tuning, PEFT techniques like LoRA, QLoRA and the strategy to adopt for various use cases Proficiency in languages such as Python, Scala, or Java In depth knowledge of both relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., Vector databases, MongoDB, Cassandra etc). Expertise in Gen AI/AI libraries / frameworks, including but not limited to LangChain, LangGraph, LangSmith, TensorFlow, PyTorch, scikit and Keras Proven understanding of cloud computing platforms (e.g., AWS, Azure, Google Cloud) and experience deploying AI models on these platforms. Proven experience in managing client relationships and understanding their business needs to deliver successful AI solutions. Strong understanding of AI systems architecture and the ability to design and implement complex AI solutions for clients across various industries. Experience with project management methodologies, and a proven ability to manage large, complex projects to successful completion. Excellent leadership, mentoring, and team building skills, with a track record of developing high performing teams. Strong business acumen, with the ability to balance technical expertise with client centric decision making. Outstanding communication and presentation skills, capable of engaging with senior executives and non-technical stakeholders. Strong problem solving and analytical skills, with the ability to think creatively and provide innovative solutions Preferred Skills: Knowledge of NVIDIA CUDA, cuDNN, TensorRT, and experience with NVIDIA GPU hardware and the software stack. Familiarity with High Performance Computing (HPC) and their integration of AI workloads. Familiarity with Big Data platforms and technologies, such as Hadoop or Apache Spark and their integration with AI solutions.

Key Responsibilities: 1. Model Development and Deployment: Design, develop, and deploy generative AI models using cutting-edge techniques and frameworks. Utilize tools like LangChain, LangGraph, LangSmith to enhance model functionality and performance. Build models on complex RAG Architecture & should be able to incorporate AI security by design. 2. Agentic AI and Intelligent Systems: Develop and integrate intelligent agents and agentic AI systems to automate and optimize processes. Collaborate with cross-functional teams to implement agent-based solutions in various applications. 3. Research and Innovation: Stay updated with the latest advancements in AI and machine learning. Experiment with new algorithms and methodologies to improve existing models and systems. 4. Collaboration and Technical Leadership: Work closely with data scientists, software engineers, and product managers to ensure AI solutions meet business needs. Provide technical guidance and mentorship to junior team members. 5. Performance Optimization and Scalability: Optimize models for efficiency, scalability, and robustness in production environments. Monitor and evaluate system performance, implementing improvements as necessary. 6. Documentation and Knowledge Sharing: Document model architectures, processes, and key findings. Share insights and advancements with the team and stakeholders. Qualifications: Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Proven experience in developing and deploying generative AI models and machine learning systems. Proficiency in programming languages such as Python, with expertise in frameworks like TensorFlow, PyTorch, or Keras. In-depth knowledge of LangChain, Langraph, LangSmith, Agents, Agentic AI, and MCP. Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization technologies (e.g., Docker, Kubernetes). Strong analytical and problem-solving skills. Excellent communication skills and ability to work collaboratively in a tea Mandatory Skills: Generative AI.Experience3-5 Years.

Tech stack required: Programming languages: Python Public Cloud: AzureFrameworks: Vector Databases such as Milvus, Qdrant/ ChromaDB, or usage of CosmosDB or MongoDB as Vector stores. Knowledge of AI Orchestration, AI evaluation and Observability Tools. Knowledge of Guardrails strategy for LLM. Knowledge on Arize or any other ML/LLM observability tool. Experience: Experience in building functional platforms using ML, CV, LLM platforms. Experience in evaluating and monitoring AI platforms in production Nice to have requirements to the candidate Excellent communication skills, both written and verbal. Strong problem-solving and critical-thinking abilities. Effective leadership and mentoring skills. Ability to collaborate with cross-functional teams and stakeholders. Strong attention to detail and a commitment to delivering high-quality solutions. Adaptability and willingness to learn new technologies. Time management and organizational skills to handle multiple projects and priorities.

Job description Job description Job Summary: We are looking for a results-driven and innovative Data Scientist with 46 years of experience in data analysis, machine learning, and product optimization. The ideal candidate will have a strong foundation in Python, SQL, and cloud services, along with practical exposure to GenAI, LLMs, and MLOps frameworks. You will be responsible for building scalable data pipelines, developing machine learning models, and solving real-world business problems with data-driven solutions. Key Responsibilities: Design and deploy LLM-powered solutions (e.g., RAG, LangChain, Vector DB) to enhance business processes. Build and fine-tune traditional ML models (Random Forest, Decision Trees) for predictive analytics. Optimize LLM performance using LoRA fine-tuning and post-training quantization. Develop and deploy containerized AI applications using Docker and FastAPI. Collaborate with agents like CrewAI and LangSmith to automate document processing and data extraction workflows. Implement Python & SQL-based ETL pipelines for real-time data ingestion. Design dashboards and KPI monitoring tools using Metabase to enable data-driven decision-making. Create data consumption triggers and automate reporting for international stakeholders. Moderate large-scale live virtual data science classes and provide operational support. Required Skills: Programming: Python, SQL, FastAPI ML & AI: Random Forest, Decision Trees, Clustering, PCA, DL, NLP, Transformers, Gen AI Frameworks/Tools: LangChain, MLflow, Kubeflow, CrewAI, LangSmith DevOps: Docker, Git Databases: MySQL, PostgreSQL, MongoDB Cloud: AWS (S3, EC2) Visualization: Metabase Other: Experience with LLM fine-tuning and quantization Role & responsibilitiesRole & responsibilities Preferred candidate profile

Project Description: Grid Dynamics aims building enterprise generative AI framework to deliver innovative, scalable and efficient AI-driven solutions across business functions.Due to constant scaling of digital capabilities the platform requires enhancements to incorporate cutting-edge generative AI features and meet emerging business demands. Platform should onboard brand new capabilities like Similarity Search (image,video and voice);Ontology and entity managment;voice and file mgmt [text to speech & vice-versa, metadata tagging, multi-media file support];Advanced RAG ; Multi-Modal capabilities Responsibilities: As an LLMOps Engineer, you will be responsible for providing expertise on overseeing the complete lifecycle management of large language models (LLM). This includes the development of strategies for deployment, continuous integration and delivery (CI/CD) processes, performance tuning, and ensuring high availability of our LLM services. You will collaborate closely with data scientists, AI/ML engineers, and IT teams to define and align LLM operations with business goals, ensuring a seamless and efficient operating model. In this role, you will: Define and disseminate LLMOps best practices. Evaluate and compare different LLMOps tools to incorporate the best practices. Stay updated on industry trends and advancements in LLM technologies and operational methodologies. Participate in architecture design/validation sessions for the Generative AI use cases with entities. Contribute to the development and expansion of GenAI use cases, including standard processes, framework, templates, libraries, and best practices around GenAI. Design, implement, and oversee the infrastructure required for the efficient operation of large language models in collaboration with client entities. Provide expertise and guidance to client entities in the development and scaling of GenAI use cases, including standard processes, framework, templates, libraries, and best practices around GenAI Serve as the expert and representative on LLMops Practices, including: (1) Developing and maintaining CI/CD pipelines for LLM deployment and updates. (2) Monitoring LLM performance, identifying and resolving bottlenecks, and implementing optimizations. (3) Ensuring the security of LLM operations through comprehensive risk assessments and the implementation of robust security measures. Collaborate with data and IT teams to facilitate data collection, preparation, and model training processes. Practical experience with training, tuning, utilizing LLMs/SLMs. Strong experience with GenAI/LLM frameworks and techniques, like guardrails, Langchain, etc. Knowledge of LLM security and observability principles. Experience of using Azure cloud services for ML Experience of using Azure cloud services for ML Min requirements: Programming languages: Python Public Cloud: Azure Frameworks: K8s, Terraform, Arize or any other ML/LLM observability tool Experience: Experience with public services like Open AI, Anthropic and similar, experience deploying open source LLMs will be a plus Tools: LangSmith/LangChain,guardrails Would be a plus: Knowledge of LLMOps best practices. Experience with monitoring/logging for production models (e.g. Prometheus, Grafana, ELK stack) We offer: Opportunity to work on bleeding-edge projects Work with a highly motivated and dedicated team Competitive salary Flexible schedule Benefits package - medical insurance, sports Corporate social events Professional development opportunities Well-equipped office