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Our team is looking for a Deep Learning Engineer.
Role and Responsibilities:
Develop Large Language Models as part of our applied research projects and in support of Platform, including designing, implementing and training massive-scale deep language models
Implement, optimize, scale and test new cutting edge ideas and architectures
Perform large-scale evaluations and comparisons of trained models across a range of benchmarks, as well as adding support for new benchmarks

We are looking for an exceptional MLOps Team Lead to own, build, and scale the infrastructure and automation that powers Labs state-of-the-art Large Language Models (LLMs) and AI systems.
This is a technical leadership role that blends hands-on engineering with strategic vision. You will define MLOps best practices, build high-performance ML infrastructure, and lead a world-class team working at the intersection of AI research and production-grade ML systems.
You will work closely with LLM Algorithm Researchers, ML Engineers, and Data Scientists to enable fast, scalable, and reliable ML workflows covering everything from distributed training to real-time inference optimization.
If you have deep technical expertise, thrive in high-scale AI environments, and want to lead the next generation of MLOps, we want to hear from you.

We are looking for a Software Engineer -A new college Grad to join our growing team!
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.

We are looking for a senior backend engineer who is truly cross functional possesses strong engineering foundations for developing highly performant services.
The ideal candidate will have a deep understanding of algorithms and Python fundamentals, as well as an understanding of the capabilities and limitations of LLMs.
They will be able to quickly collaborate with their product counterparts to iterate over new, cutting edge features and capabilities and get them to the hands of our users.
Collaborating closely with product teams, they will quickly ideate, develop and deliver innovative features and capabilities to our users.
If you have the skills and experience we are looking for, we encourage you to apply for this exciting opportunity to join our team and make a significant impact on the future of AI.
Role and Responsibilities:
Build the framework used to supercharge our algorithm teams to write scalable, performant algorithms
E2E ownership of production services, databases and infrastructure
Work in fast iteration loops with business/product managers to architect and deliver new products and capabilities
Drive the architectural design, including dependent services and service interactions (APIs & SDKs)
Apply judgment and experience to balance trade-offs between competing interests and optional solutions, considering profiling data to inform decisions on performance and resource utilization
Help with coaching and mentoring team members, and maintaining high standards of software quality within the team.

We are looking for a creative and impact-driven Software Engineer Solutions to join our Solutions team. This is a hands-on role at the forefront of Generative AI adoption, where you will design and implement real-world solutions built on products, including Maestro and Jamba.
Youll combine deep technical skills with strong interpersonal abilities becoming an expert in Large Language Models (LLMs), guiding strategic accounts as a trusted advisor, and collaborating closely with clients product and engineering teams. Your work will not only deliver business impact for customers, but also shape= product roadmap through the insights and best practices you bring back from the field.
Role and Responsibilities
Gain an in-depth understanding of client goals and constraints and translate them into technical specifications
Design and implement effective solutions using models and APIs including writing code, integrating APIs and building scalable pipelines
Own the technical delivery across the customer lifecycle, from proof-of-concept to production deployment, scaling, monitoring, and ongoing optimization engaging R&D teams where deeper specialization is required
Partner with Customer Success and Sales to drive successful engagements, supporting both new opportunities and expansion of existing use cases
Act as the customers trusted advisor, while channeling feedback, challenges, and opportunities from the field to Product to guide roadmap decisions
Gather client feedback to highlight challenges and opportunities, driving model improvements and shaping the product roadmap

Our finance team is growing and we are looking for an experienced controller to join our team.
The controller will be a key position within the finance department, reporting to the Director of Finance.
Role and Responsibilities:
Preparation of monthly, quarterly and annual financial statements in accordance with US- GAAP
Conduct month end closing procedures
Enhance and implement financial and accounting systems, processes and controls.
Work closely with the FP&A team to track the budget and maintain a budget vs. actual analysis.
Oversight of the billing cycle including revenue recognition (SAAS and On-Prem), invoicing, collections and revenue metrics.
Preparation of annual tax returns for the Parent company and its US subsidiary, including tax filings and reporting requirements.
Coordinate with external auditors, bookkeepers, banks and other third-party vendors.
Ensure compliance with all regulatory requirements and accounting standards.
Assist in monitoring and maintaining the companys KPIs.

We are seeking an experienced Solutions Data Engineer who possess both technical depth and strong interpersonal skills to partner with internal and external teams to develop scalable, flexible, and cutting-edge solutions. Solutions Engineers collaborate with operations and business development to help craft solutions to meet customer business problems.
A Solutions Engineer works to balance various aspects of the project, from safety to design. Additionally, a Solutions Engineer researches advanced technology regarding best practices in the field and seek to find cost-effective solutions.
Job Description:
Were looking for a Solutions Engineer with deep experience in Big Data technologies, real-time data pipelines, and scalable infrastructuresomeone whos been delivering critical systems under pressure, and knows what it takes to bring complex data architectures to life. This isnt just about checking boxes on tech stacksits about solving real-world data problems, collaborating with smart people, and building robust, future-proof solutions.
In this role, youll partner closely with engineering, product, and customers to design and deliver high-impact systems that move, transform, and serve data at scale. Youll help customers architect pipelines that are not only performant and cost-efficient but also easy to operate and evolve.
We want someone whos comfortable switching hats between low-level debugging, high-level architecture, and communicating clearly with stakeholders of all technical levels.
Key Responsibilities:
Build distributed data pipelines using technologies like Kafka, Spark (batch & streaming), Python, Trino, Airflow, and S3-compatible data lakesdesigned for scale, modularity, and seamless integration across real-time and batch workloads.
Design, deploy, and troubleshoot hybrid cloud/on-prem environments using Terraform, Docker, Kubernetes, and CI/CD automation tools.
Implement event-driven and serverless workflows with precise control over latency, throughput, and fault tolerance trade-offs.
Create technical guides, architecture docs, and demo pipelines to support onboarding, evangelize best practices, and accelerate adoption across engineering, product, and customer-facing teams.
Integrate data validation, observability tools, and governance directly into the pipeline lifecycle.
Own end-to-end platform lifecycle: ingestion → transformation → storage (Parquet/ORC on S3) → compute layer (Trino/Spark).
Benchmark and tune storage backends (S3/NFS/SMB) and compute layers for throughput, latency, and scalability using production datasets.
Work cross-functionally with R&D to push performance limits across interactive, streaming, and ML-ready analytics workloads.
Operate and debug object storebacked data lake infrastructure, enabling schema-on-read access, high-throughput ingestion, advanced searching strategies, and performance tuning for large-scale workloads.