Driven to make a difference as a Senior Machine Learning Engineer in the tech industry? We are on the lookout for an individual with a passionate commitment, a wealth of skill in machine learning and data engineering, and a readiness to unleash groundbreaking models. Join our ranks if you find satisfaction in navigating through complex systems and achieving consequential results. In our fold, your role will extend beyond machine learning, mandating a cooperative interaction with diverse teams to engineer strategic resolutions. Our workspace champions innovative thought and provides a supportive environment, fostering growth at every turn. If you're eager to significantly contribute to transformative projects and accelerate your career, you may just be the visionary we seek. Embark on this thrilling voyage of discovery and reinvention with us. Your dream job is just a decision away!
responsibilities
Work with DevOps/System engineers to automate necessary infrastructure provisioning
Contribute to creating ML platforms
Converting machine learning models and algorithms prototypes into production ready optimized ML pipelines
Contribute to ML pipeline design and development (including validation and cold start problem, A/B tests, feedback loop, etc)
Create from scratch, maintain, troubleshoot, and optimize ML pipeline steps
Optimizing / tuning ML models and ML pipelines to satisfy production environment requirements
Automating key parts of CICD pipelines for ML pipelines
Collaborating with data scientists to fine-tune and optimize models
Write specifications, documentation, and user guides for developed solutions
Integrating ML models into existing software systems or creating new applications
Allocate activities to junior ML engineers and take tasks to closure
Improvise coding practices, support code reviews and bring in best practices for model management
requirements
At least 5 years of production experience working in MLE role
At least one project delivered to production in MLE role
Expert level in Engineering Best Practices
Advanced knowledge of Machine Learning fundamentals
Production experience in integrating ML models into complex data-driven systems
Experience with of Python ML ecosystem
Practical experience working with at least one of the major Cloud Provider such as AWS, GCP, Azure
Experience with one of the MLOps related platform/technology such as AWS SageMaker, Azure ML, GCP Vertex, Databricks MLFlow, Kubeflow, TensorFlow Extended
We are looking for a Senior/Lead AI Engineer to join our team in building a central GenAI Platform that enables hundreds of product teams across the organization to rapidly develop, validate, and deploy AI agents at scale. You will be part of a 100-engineer team in a dynamic, innovative environment that combines the stability of an established company with the agility of a startup. In this high-impact role, you will shape platform capabilities, design full-stack systems, and drive the delivery of AI agents that foster innovation and deliver real impact across industries.
responsibilities
Design and implement full-stack applications, AI agents, and platform components to enable rapid development and deployment of GenAI solutions
Build developer tooling, CI/CD pipelines, and observability systems to ensure fast and safe iteration
Apply secure SDLC and privacy-by-design principles, including threat modeling and ensuring least privilege
Collaborate with product teams, UX designers, and domain experts to deliver customer-focused and outcome-driven solutions
Utilize state-of-the-art LLM patterns to enhance system reliability, reduce costs, and improve trust and safety metrics
Lead by example by writing high-quality, maintainable code that reflects engineering excellence
Drive the design and implementation of innovative solutions leveraging cloud services
Contribute to creating scalable, cloud-native systems for production environments
requirements
A minimum of 5 years of professional experience in software engineering
Proficiency in full-stack development and experience with cloud platforms such as AWS, Azure, or GCP
Strong expertise in at least one area, including AI agent development, backend engineering, or frontend development, with skills spanning multiple domains
Knowledge of CI/CD pipelines, Infrastructure as Code, SRE, and scalable system design
Demonstrated success in building and delivering robust and secure cloud-native systems
Understanding of secure SDLC principles, data privacy considerations, and advanced quality engineering approaches
Strong problem-solving skills and the ability to communicate effectively across various teams
Upper-Intermediate English language proficiency (B2+)
nice to have
Proven ability to take software products from concept to completion in fast-paced environments
Demonstrated experience in developing AI agents, including safety assessments, iterative testing, and continuous optimization
Familiarity with LangChain, LangGraph, vector search systems, and OpenSearch
Knowledge of traditional ML processes like model training, deployment, and monitoring
Understanding of LLM architecture, failure modes, fine-tuning strategies, and model adaptation techniques
Awareness of regulatory standards such as SOC2 or HIPAA
We are seeking a dynamic Senior BI Analyst to join our team and drive data-led decision-making by crafting actionable insights and delivering high-quality data solutions. The ideal candidate will have a strong background in business intelligence, data modeling, and project delivery, enabling them to collaborate effortlessly with stakeholders and technical teams.
responsibilities
Lead stakeholder workshops to define and prioritize business needs
Translate requirements into actionable insights, fostering seamless collaboration with the delivery team throughout the project lifecycle
Perform data discovery, data assessment and data profiling using SQL queries
Prepare source to target mappings, data models and data flows
Validate prototype for business alignment using mock-ups
Conduct Sprint review sessions or User Acceptance Testing with customer stakeholders
Collaborate with customer stakeholders in designing data products
Prepare post-development and post-production materials
requirements
5+ years of experience in data-related projects (e.g., data migration, data transformation, data governance, etc.)
3+ years of expertise in handling BI, DWH, data and analytical project requirements (gathering, documenting, presenting, estimating, prioritizing, etc.)
Experience in data governance
Proficiency in end-to-end data and analytics project delivery using Agile and waterfall methodologies
Expertise in defining and organizing backlogs, including epics, features, and stories
Deep understanding of data modeling and data quality
Proficiency in performing data profiling using SQL queries and conducting data quality analysis
Experience in preparing source-to-target mappings for data ingestion, curation, and related processes
Excellent command of written and spoken English (B2+ level)
nice to have
Experience with data on cloud platforms like Azure, AWS and GCP
Skills in creating data prototypes
Industry knowledge in finance, insurance, oil and gas, supply chain or marketing
Ability to act as a Product Owner or Data Product Owner in analytical projects
We are looking for a highly motivated remote Lead Cloud Engineer to join our Site Reliability team, working closely with our internal users and development teams to ensure production systems stability in a highly competitive environment. In this role, you will be responsible for building and maintaining our cloud platforms and support applications while demonstrating agile and dynamic application support capabilities. You will collaborate closely with other internal technical teams and business users in investigating, testing, and deployments, contributing to the continuous improvement and delivery of our DevOps practices. If you are passionate about DevOps, cloud platforms, and automation, we invite you to be part of our team.
responsibilities
Build and maintain our cloud platforms and support applications, demonstrating agile and dynamic application support capabilities.
Contribute in our continuous improvement and continuous delivery while increasing maturity of DevOps practices.
Contribute in developing and implementing automated DevOps capability for our application.
Collaborate closely with other internal technical teams/business users in investigating, testing and deployments
Responsible for handling Release Management, raising Change Request and scheduling for the implementation of fixes and enhancements.
Work effectively in collaboration with different teams either local or remote.
Work towards 100% availability of our applications by putting in right monitoring in place.
Support our production environment with strong performance tuning, end-to-end troubleshooting, networking fundamentals skills.
Willingness to work efficiently during the events thereby making sure that the event is a success.
requirements
Bachelor’s Degree/Diploma in Computer Science, Computer Engineering, or Computer Application
5+ years’ experience as a DevOps engineer supporting modern stack (AWS, PCF, containers, or Kubernetes)
1+ year of team leading experience
Hands-on Experience in one or more of the following: Java Script, Java and Python.
Hands-on Experience with one of more of ELK, Grafana, AppDynamics, Kibana.
Hands-on Experience with CI/CD pipelines and release strategies
Strong, committed and reliable team player, able to take direction but also willing to contribute to discussions on design and strategy.
Fluent spoken and written English at an Upper-Intermediate level or higher, enabling effective communication
We are looking for a driven and skilled Senior Python Developer to join our dynamic team. In this role, you will architect and implement robust data engineering solutions, leveraging your expertise in Python, cloud platforms, and modern tools to build scalable systems. You will collaborate with cross-functional teams to deliver innovative solutions while following Agile best practices.
responsibilities
Develop and implement complex data engineering solutions using Python
Utilize Apache Spark for efficient data processing and analytics
Design and maintain cloud-based solutions with platforms like AWS or Azure
Collaborate with stakeholders and teams to align on requirements, goals, and deliverables
Apply Agile frameworks and SDLC principles to drive efficient software development processes
Enhance automation frameworks using robust CI/CD tools
Monitor, troubleshoot, and optimize data pipelines and workflows
Support technical decision-making through analysis and best practices
Mentor junior developers and share knowledge across teams
requirements
5+ years of professional experience with Python in a development environment
Proven expertise in building and maintaining scalable data engineering workflows
Proficiency with Apache Spark for real-time and batch data processing
Hands-on experience with cloud platforms such as AWS or Azure
Solid familiarity with Agile frameworks and the Software Development Life Cycle (SDLC)
Competency with CI/CD tools to streamline deployment pipelines
Good command of English at a B2 level or higher for effective communication
nice to have
Familiarity with Apache Airflow for orchestrating workflows
Knowledge of Databricks for enhancing collaborative workflows in data and AI projects
Understanding of Generative AI (GenAI) and Machine Learning tools for improving intelligent solutions
Are you prescribed to redefine the vanguard of technological innovation as a Lead Machine Learning Engineer ? We are scouting for a zealot, proficient in machine learning and data engineering, poised to create transformative solutions. Join us if you delight in maneuvering complex systems and yearn to make influential strides. Here, your role will traverse beyond machine learning, collaboratively engaging with diverse teams to arrive at strategic breakthroughs. We foster an immersive, innovative atmosphere that nurtures professional ascent and celebrates every victory. If the thought of architecting landmark projects and advancing in your career fuels your ambition, you might be the linchpin we are in search of. Embark on this exhilarating expedition of uncovering and forging novel technological pathways. Your much-aspired professional destination awaits you!
responsibilities
Own and contribute to ML pipeline design, development, and operating lifecycle based on best practices
Design, develop and deploy complex AI/ML solutions on cloud infrastructure (using ML engineering, ML Ops workflows & tools) that can scale in response to changing business and technical requirements
Create infrastructure and architecture diagrams
Own collaboration with data scientists and engineering team to optimize ML pipeline performance
Allocate activities to junior ML engineers and take tasks to closure
Improvise coding practices, support code reviews and bring in best practices for model management
Provide thought leadership in terms of new technologies and tools, suggest improvements
Support the interview process to hire junior and senior ML engineers
requirements
Experience in AI/ML engineering and leadership
Proficiency in moving complex AI/ML solutions to production
Practical experience with Apache Spark Ecosystem
Knowledge of best practices in software engineering, data management, testing and deployment
Expertise in building scalable, reliable and maintainable ML systems
Strong communication and interpersonal skills to liaise with senior business stakeholders, customers and team members
Ability to work in a fast-paced, deadline-driven environment, mentor and guide junior team members and provide technical leadership
Strong knowledge and experience in Python development
Experience with cloud native services: GCP, AWS, Azure
Experience with some of the MLOps related platform/technology such as AWS SageMaker, Azure ML, GCP Vertex AI / AI Platform, Databricks MLFlow, Kubeflow, Airflow, TensorFlow Extended
Strong written and verbal English communication skills (B2+)
We are seeking a Lead AI Engineer to join our team and drive the development of cutting-edge AI solutions. This role involves designing and implementing full-stack applications, AI agents, and platform components to enable rapid GenAI agent development, validation, and deployment.
responsibilities
Design and implement full-stack applications, AI agents, and platform components
Build developer tooling, CI/CD, and observability for safe, fast iteration
Apply secure SDLC and privacy-by-design practices
Collaborate with product, UX, and domain experts to deliver customer-focused solutions
Apply current LLM patterns to deliver measurable customer value
Lead by example, drive architecture, mentor engineers, and take ownership of larger projects
requirements
5+ years of professional software engineering experience
Strong full-stack development skills and cloud experience (AWS/Azure/GCP)
Expert in at least one, and proficient across the others: AI Agent development and evaluation, Backend development, Frontend development
Cloud services (AWS/Azure/GCP), CI/CD and Infrastructure as Code, Site Reliability Engineering (SRE)
Quality engineering/testing strategy, Secure SDLC and privacy by design
Proven track record delivering secure, reliable, cloud-native systems to production
Upper-Intermediate English language proficiency (B2)
nice to have
Proven ability to deliver software products independently or as part of a small, fast-paced team
Experience of taking AI agents from concept to production, including safety evaluations and iterative testing
Experience with LangChain/LangGraph and MCP; vector/RAG systems; OpenSearch
Worked on traditional ML tasks like training, deployment, and monitoring
Understand how LLMs work, their failure modes, and techniques like fine-tuning and model adaptation
Familiarity with regulatory frameworks such as SOC2, HIPAA, etc.
We are seeking a Senior AI Engineer to create and implement advanced AI applications, including chatbots, Q&A systems, and agent workflows. This position requires keeping pace with advancements in LLM technologies and driving innovation in AI projects. Join us to enhance your skills in AI engineering and deliver impactful solutions tailored to client needs.
responsibilities
Design AI applications such as chatbots, Q&A platforms, and agent workflows
Collaborate with clients to understand requirements, identify opportunities, and propose LLM-driven solutions
Build data pipelines, prompt strategies, and datasets to optimize AI models
Optimize AI system performance to ensure security, scalability, and compliance with industry standards
Conduct research and develop prototypes to validate feasibility and prove business value
Evaluate LLM advancements, frameworks, and methodologies to improve solutions for client needs
requirements
3+ years of experience in Python, with web frameworks like FastAPI or similar
Understanding of AI application development lifecycle
Background in rapid UI prototyping using tools like Streamlit or Gradio
Familiarity with major LLM platforms and APIs like OpenAI, Anthropic, Amazon Bedrock, and Gemini, alongside related frameworks such as LangGraph, LlamaIndex
Knowledge of integration techniques like RAG and Agents
Proficiency in deploying AI solutions at scale with attention to performance and maintainability
Skills in evaluating generative AI quality with metrics like retrieval and classification scores
Expertise in AI engineering and delivering machine learning solutions
Competency in problem-solving with a strong attention to detail
Clear communication and collaboration abilities with demonstrated interpersonal skills
nice to have
Expertise in experiment design and utilizing A/B tests to refine models based on feedback
Understanding of retrieval systems like keyword search, vector search, and embeddings, along with ranking algorithms
Familiarity with emerging protocols like MCP, A2A, and ACP
Capability to deploy to platforms like Azure OpenAI, Amazon Bedrock, GCP Vertex AI, or on-premise setups like vLLM
Background in enterprise AI solutions including AWS AgentCore, Databricks AgentBricks, Google Agents Space, or Azure AI Foundry
Proficiency in using observability and monitoring tools effectively
technologies
Python, PyTorch, Hugging Face, LangChain
Vector databases including Qdrant, FAISS, Chroma
APIs for LLMs such as Azure OpenAI and AWS Bedrock
We are seeking a Senior AI Engineer to design and develop comprehensive AI applications, including chatbots, Q&A systems, and agent workflows. This role involves staying updated with the latest LLM technologies and contributing to innovative AI projects. Join our team to advance your expertise in AI engineering and deliver impactful solutions that meet client needs.
responsibilities
Design, implement, and maintain end-to-end AI applications, including chatbots, Q&A platforms, and agent workflows
Collaborate directly with clients to understand their needs, identify opportunities, and recommend LLM-driven solutions
Develop and manage robust data pipelines, prompt strategies, and datasets to ensure effective and accurate AI models (Will be a plus)
Evaluate and refine AI system performance, ensuring outputs are accurate, secure, scalable, and compliant with industry regulations (Will be a plus)
Conduct research and rapid prototyping to validate technical feasibility and demonstrate business value of AI solutions
Stay current with evolving LLM technologies, frameworks, and methodologies to continuously improve solutions and client outcomes
requirements
Strong proficiency in Python, experience with web frameworks like FastAPI or similar
Understanding of the AI application development lifecycle
Experience with rapid UI prototyping using Streamlit, Gradio, or similar frameworks
Familiarity with major LLM platforms and APIs (OpenAI, Anthropic, Amazon Bedrock, Gemini) and related frameworks (LangGraph, LlamaIndex, Strands Agents, etc.)
Knowledge of advanced AI integration patterns (e.g., RAG, Agents)
Experience deploying AI solutions at scale, with considerations for performance, cost-efficiency, and maintainability
Proven ability to evaluate generative AI quality using metrics such as retrieval and classification scores, as well as LLM-based evaluation methods
Proven experience in AI engineering and delivering ML-based solutions
Strong problem-solving skills and attention to detail
Excellent communication, collaboration, and interpersonal skills
nice to have
Experience designing experiments, conducting A/B tests, and iterating on models based on user feedback
Understanding of retrieval systems (keyword search, vector search, embeddings) and ranking algorithms
Familiarity with emerging protocols such as MCP, A2A, ACP, etc.
Experience deploying to cloud AI platforms (Azure OpenAI, Amazon Bedrock, GCP Vertex AI) or on-premise solutions (e.g., vLLM)
Experience with enterprise AI platforms such as AWS AgentCore or Databricks AgentBricks or Google Agents Space, or Azure AI Foundry
Experience with observability and monitoring tools and frameworks
technologies
Python, PyTorch, Hugging Face, LangChain
Vector databases including Qdrant, FAISS, Chroma
APIs for LLMs such as Azure OpenAI and AWS Bedrock
We are looking for a skilled and innovation-focused Lead AI Engineer to lead the creation of advanced generative AI solutions. If you are passionate about artificial intelligence and experienced in building systems that drive tangible business outcomes, this role is for you. Join a dynamic team and develop AI-driven technologies that solve real-world problems in a collaborative and future-oriented setting.
responsibilities
Design and maintain AI applications such as chatbots, Q&A platforms, and agent workflows
Collaborate with clients to understand needs, identify opportunities, and propose LLM-powered solutions
Build and optimize data pipelines, prompt strategies, and datasets for reliable and effective AI models
Conduct research and prototyping to validate technical feasibility and demonstrate AI solutions' business value
Optimize AI system performance for accuracy, security, scalability, and industry compliance
Stay informed about advancements in LLM technologies, frameworks, and methodologies to enhance outcomes
requirements
5+ years of experience in Python, with web frameworks like FastAPI or similar
1+ years of leadership experience
Background in AI application development lifecycle
Skills in rapid UI prototyping using Streamlit, Gradio, or similar frameworks
Familiarity with major LLM platforms and APIs (OpenAI, Anthropic, Amazon Bedrock, Gemini) and related frameworks (e.g., LangGraph, LlamaIndex)
Knowledge of advanced AI integration patterns (e.g., RAG, Agents)
Proficiency in deploying scalable AI solutions with cost and performance considerations
Proven ability to assess generative AI quality using retrieval/classification scores and LLM-based evaluation methods
Expertise in AI engineering and implementing ML-driven solutions
Competency in problem-solving with strong attention to detail
Effective communication, collaboration, and interpersonal skills
nice to have
Skills in designing experiments and conducting A/B tests with iterative model improvements
Understanding of retrieval systems (e.g., keyword search, vector search, embeddings) and ranking algorithms
Knowledge of emerging protocols such as MCP, A2A, and ACP
Proficiency in deploying cloud AI platforms (Azure OpenAI, Amazon Bedrock, GCP Vertex AI) or on-premise solutions (e.g., vLLM)
Background in enterprise AI platforms such as AWS AgentCore, Databricks AgentBricks, Google Agents Space, or Azure AI Foundry
Familiarity with observability and monitoring tools or frameworks
technologies
Python, PyTorch, Hugging Face, LangChain
Vector databases including Qdrant, FAISS, Chroma
APIs for LLMs such as Azure OpenAI and AWS Bedrock
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