Current Openings

Job ID : 0001

USA 8+ Full-Time

We are seeking a skilled AI back-end developer. You will be responsible for developing and maintaining high-quality software products, working with a variety of programming languages and technologies.

Responsibilities:

• Lead AI Solution Design: Oversee the end-to-end design of AI solutions covering data acquisition, pre-processing, model selection, training, deployment, and ongoing maintenance.
• Data Quality Management: Manage the cleaning, pre-processing, and curation of extensive datasets to ensure high-quality data for effective AI model training and validation.
• Prototype Development: Create prototypes and proof-of-concepts to showcase the feasibility of proposed AI solutions, gaining stakeholder buy-in and support.
• Collaborative Integration: Work closely with cross-functional teams including data engineers, software developers, product managers, and domain experts to align AI solutions with overall product development strategies.
• Model Optimization: Train and fine-tune AI models using advanced techniques and frameworks. Evaluate model performance using relevant metrics, iteratively refining models for improved accuracy and efficiency.
• Mentorship and Guidance: Provide mentorship and guidance to AI developers, data scientists, and engineers, ensuring adherence to industry best practices and architectural guidelines.
• Emerging Technology Evaluation: Stay updated with emerging AI technologies, tools, and frameworks, assessing their suitability in resolving specific business challenges.

Experience:

• The ideal candidate should possess over 5 years of experience in developing enterprise applications using Java, Python, Scala, Spark, and related technologies, with a focus on Data Engineering and ML Ops for at least 2 years.
• They should demonstrate hands-on experience with common distributed processing tools and languages like Python, Spark, Hive, and Presto.
• A comprehensive understanding of data best practices and expertise in ML/DevOps implementation within SaaS and hybrid environments is required.
• A strong grasp of data governance, data security, and the implementation of data privacy best practices is essential.
• Familiarity with pipeline orchestrator tools such as Argo, Kubeflow, Airflow, or other open-source alternatives is expected.
• Experience with specialized data architectures like data lakes, data mesh, and optimizing data layouts for efficient processing is highly desirable.
• Additionally, familiarity with platforms like Kubernetes and practical experience in building on top of native platforms would be beneficial.
• Experience with cloud-based data platforms and services (e.g., AWS, Azure, Google Cloud).
• Excellent communication skills are a must, enabling effective collaboration with both technical and non-technical stakeholders.
• Strong ability to provide guidance to less experienced team members.

Job ID : 0002

USA 8+ Full-Time

We're seeking a highly skilled Machine Learning Engineer to optimize our systems. You'll evaluate existing ML processes, conduct statistical analysis to address dataset issues, and enhance our AI software's predictive capabilities.

Successful candidates will possess robust data science expertise and related ML experience. A top-notch ML Engineer will significantly boost predictive automation software performance.

Responsibilities:

• Collaborate with managers to define and refine machine learning objectives.
• Design ML systems and autonomous AI software for predictive model automation.
• Translate data science prototypes into applicable ML algorithms and tools.
• Ensure precise user recommendations through algorithm accuracy.
• Convert unstructured data into actionable insights via image auto-tagging and text-to-speech conversion.
• Tackle complex problems within multi-layered datasets, optimizing existing ML frameworks.
• Develop ML algorithms analyzing extensive historical data for predictive purposes.
• Conduct tests, perform statistical analysis, and interpret test outcomes.
• Document machine learning processes thoroughly.
• Stay updated on machine learning advancements.

Experience Requirements:

• Bachelor's in Computer Science, Data Science, Mathematics, or a related field.
• Master’s in Computational Linguistics, Data Analytics, or similar advantageous.
• Minimum two years' experience as a Machine Learning Engineer.
• Proficiency in Python, Java, and R coding.
• Extensive knowledge of ML frameworks, libraries, data structures, and software architecture.
• Deep understanding of mathematics, statistics, and algorithms.
• Strong analytical and problem-solving skills.
• Excellent communication, collaboration, time management, and organizational abilities.

Job ID : 00003

Virtual – USA 7+ Full-Time

Responsibilities:

• Ensure proper monitoring and analysis of logs, alerts, and external data sources to determine any security and operational impact to the organization.
• Define and assess cybersecurity strategy with the CISO and CIO.
• Monitor strategy implementation and adherence to cyber policies, standards and procedures. Provide input and help guide enterprise-wide cybersecurity awareness and communications campaigns. 
• Resolve or escalate cyber security incidents and events and escalate to the Incident Response team as needed per established guidelines. Review research performed by SOC Analysts related to security events and threat intelligence data.
• Collaborate within the SOC and across IT to mature SOC playbooks, alerting, processes, and Incident Response actions.
• Perform proactive threat research and validation for security event data generated from monitoring tools and manual analysis. Review all IR tickets to ensure accuracy and completeness.
• Create metrics based on the offenses handled and work performed by the Security Operations.
• Maintain Security Operations metrics dashboards.
• Create Reference Sets within the SIEM tool to assist Tier 1 and 2 SOC Analysts with threat research.
• Perform documentation of event analysis and records the data within our Incident Tracking tool. Represent the Security Operations team in various SOC, Incident Response, and Cyber Security projects.
• Provide guidance to the organization to help advance defensive capabilities, including cyber security technologies, enterprise security platforms, and incident response processes and procedures.
• Act as an escalation point and technical lead for the SOC II team. Provide leadership and oversight to the SOC I team responsible for investigating all security related anomalies presented by enterprise security platforms.
• Must be able to provide on call support for process related issues, technical issues with security platforms, and VF non-security related high severity incidents.

Experience:

• Bachelor's Degree (or equivalent) in Computer Science, Information Technology, Cyber Security, or related discipline.
• Proven leadership skills, with demonstratable experience in coaching and mentoring junior members within a small team.
• Minimum of 6+- years of experience in roles related to cyber security operations or DLP operations.
• Knowledge of general attack stages, attacker Techniques, Tactics, and Procedures (TTPs), and defense models.
• Hands on technical experience with CASB, DLP, Web Proxy, SIEM, E-Discovery, CSPM, SSPM, File and Removable media protection tools (FRP).
• Hands on experience with Data Classification policies and technologies to address data leakage.
• Excellent interpersonal, verbal, and written communication skills with the ability to communicate security risk and compliance related concepts to a technical and non-technical audience.
• Information Security Certification preferred.

Virtual - USA 8+ Full-Time

Responsibilities:

• Substantial experience in large-scale AI training.
• Profound comprehension of diverse machine learning algorithms and modeling techniques such as semi-supervised or weakly supervised learning, generative models, transfer learning, optimization, large language models, etc.
• Proven track record in devising machine learning solutions utilizing extensive real-world data to tackle genuine business challenges.
• Proficiency in PyTorch/TensorFlow with hands-on experience.
• Expertise in developing data analytics and applications within production environments.
• Exceptional planning, organizational, and time management skills, including adeptness in handling product budgets, timelines, and schedules.
• Meticulous attention to detail with a strong inclination toward structured work processes.
• Ability to work autonomously while collaborating with diverse stakeholders across different geographical locations and organizational levels.
• Capability to manage multiple parallel features, adept at prioritization, and balancing tasks effectively.
• Strong leadership qualities and adeptness in managing relationships.
• Skilled in leading and influencing others to accomplish shared objectives.
• Familiarity with integration technologies, particularly APIs, is advantageous.
• Demonstrated experience and competence in addressing challenges stemming from vague or abstract problem definitions.

Minimum Qualifications:

• Bachelor's Degree in IT or a related field.
• Proven experience working extensively with large-scale AI training.
• Comprehensive knowledge of various machine learning techniques like semi-supervised or weakly supervised learning, generative models, transfer learning, optimization, large language models, etc.
• Track record of successfully developing machine learning solutions using huge real-world data to solve practical business problems.
• Profound expertise in PyTorch or TensorFlow.
• Hands-on experience in creating data analytics and applications within production settings.
• Strong skills in planning, organizing, and managing time, including handling product budgets, schedules, and timelines effectively.
• Detail-oriented with a focus on structured work processes.
• Ability to work independently while collaborating with multiple stakeholders across different locations and organizational levels.

Virtual - USA 8+ Full-Time

In this role, you will build and deploy GenAI enabled applications, fine tune and build Generative AI models, and help enterprise leverage these models.   

Experience:

• Minimum 2 years of experience as a data scientist.
• Over 3 years of experience using tools and techniques for machine learning and statistical modeling, understanding how different parameters influence their performance.
• A Master's degree in a quantitative field like statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science.
• At least 2 years of practical experience in researching and applying large language and generative AI models.
• Practical hands-on expertise in creating models, optimizing their training, fine-tuning, and deploying Large Language Models (LLMs) such as GPT, LLaMA, Falcon, BERT, or other Transformer-based architectures.
• A solid foundation in Natural Language Processing (NLP), including working knowledge of text representation, language modeling, sequence-to-sequence architectures, and understanding semantic meaning.
• Over 3 years of experience in technical architecture, design, deployment, and operational-level understanding.

Virtual - USA 7+ Full-Time

Key Responsibilities:

In this role, your main tasks will include analyzing, designing, setting up, testing, and implementing Workday HR solutions to fulfill clients' business needs. You'll also offer expertise and advice to clients on the best practices, system setup, and integration of Workday with other systems by collaborating with technical consultants.

Skills and Qualifications:

• 4-6 years of relevant experience working with Workday systems.
• Advanced knowledge of HR processes and experience collaborating with global teams.
• Proficiency in hands-on Workday modules such as Core HCM, Core and Compensation, and Security.
• Additional knowledge in modules like Benefits, Recruiting, Learning, Time, and Absence is beneficial.
• Strong presentation, communication, listening, and advisory skills to lead and facilitate discussions.
• Keeping updated with the latest Workday releases, best practices, and industry trends to deliver effective solutions to clients.